@article{Santucci2021,
author = {Santucci, V. and Baioletti, M. and Di Bari, G.},
title = {An improved memetic algebraic differential evolution for solving the multidimensional two-way number partitioning problem},
journal = {Expert Systems with Applications},
year = {2021},
volume = {178},
doi = {10.1016/j.eswa.2021.114938},
art_number = {114938},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85106346714&doi=10.1016%2fj.eswa.2021.114938&partnerID=40&md5=ebf548daa1f1c8c2fe3b5efdcd6b6a5a},
abstract = {In this article, we propose a novel and effective evolutionary algorithm for the challenging combinatorial optimization problem known as Multidimensional Two-Way Number Partitioning Problem (MDTWNPP). Since the MDTWNPP has been proven to be NP-hard, in the recent years, it has been increasingly addressed by means of meta-heuristic approaches. Nevertheless, previous proposals in literature do not make full use of critical problem information that may improve the effectiveness of the search. Here, we bridge this gap by designing an improved Memetic Algebraic Differential Evolution (iMADEB) algorithm that incorporates critical information about the problem. In particular, iMADEB evolves a population of candidate local optimal solutions by adopting three key design concepts: a novel non-redundant bit-string representation which maps population individuals one-to-one to MDTWNPP solutions, a smoother local search operator purposely designed for the MDTWNPP landscapes, and a self-adaptive algebraic differential mutation scheme built on the basis of the Lévy flight concept which automatically regulates the exploration-exploitation trade-off of the search. Computational experiments have been conducted on a widely accepted benchmark suite for the MDTWNPP with a twofold purpose: analyzing the robustness of iMADEB and compare its effectiveness with respect to the state-of-the-art approaches to date for the MDTWNPP. The experimental results provide important indications about iMADEB robustness and, most importantly, clearly show that iMADEB is the new state-of-the-art algorithm for the MDTWNPP. © 2021 Elsevier Ltd},
author_keywords = {Algebraic Differential Evolution; Combinatorial optimization; Memetic Algorithm; Multidimensional Two-Way Number Partitioning},
keywords = {Algebra; Bridges; Economic and social effects; Evolutionary algorithms; Heuristic algorithms; Heuristic methods, Algebraic differential evolution; Combinatorial optimization problems; Differential Evolution; Memetic; Memetic algorithms; Multidimensional two-way number partitioning; NP-hard; Number partitioning problems; Optimisations; Two ways, Combinatorial optimization},
publisher = {Elsevier Ltd},
document_type = {Article},
source = {Scopus}
}
@article{Agresta2021795,
author = {Agresta, A. and Baioletti, M. and Biscarini, C. and Milani, A. and Santucci, V.},
title = {Evolutionary Algorithms for Roughness Coefficient Estimation in River Flow Analyses},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2021},
volume = {12694 LNCS},
pages = {795-811},
doi = {10.1007/978-3-030-72699-7_50},
note = {Conference of 24th International Conference on the Applications of Evolutionary Computation, EvoApplications 2021 held as Part of EvoStar 2021 ; Conference Date: 7 April 2021 Through 9 April 2021; Conference Code:257359},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107490675&doi=10.1007%2f978-3-030-72699-7_50&partnerID=40&md5=f75536d0174d91aae9a71f9696499814},
abstract = {Management and analyses of water resources is of paramount importance in the implementation of water related sustainable development goals. Hydraulic models are key in flood forecasting and simulation applied to a river flood analysis and risk prediction and an accurate estimation of the roughness is one of the main factors in predicting the discharge in a stream. In practical implementation roughness can be represented by the prediction of the well known Manning’s coefficient necessary for discharge calculation. In this paper we design an objective function that measures the quality of a given configuration of the Manning’s coefficient. Such an objective function is optimised through several evolutionary approaches, namely: (1+1)-ES, CMA-ES, Differential Evolution, Particle Swarm Optimization and Bayesian Optimization. As case of study, a river in the central Italy was considered. The results indicate that the model, consistent with the classical techniques adopted in the hydraulic engineering field, is applicable to natural rivers and is able to provide an estimation of the roughness coefficients with a satisfactory accuracy. A comparison of the performances of the five evolutionary algorithms is also proposed. © 2021, Springer Nature Switzerland AG.},
author_keywords = {Estimating Manning’s coefficient; Evolutionary algorithms; River flow analysis},
keywords = {Flood control; Floods; Forecasting; Hydraulic models; Particle swarm optimization (PSO); Risk analysis; Risk assessment; Risk perception; Shore protection, Bayesian optimization; Classical techniques; Differential Evolution; Discharge calculation; Evolutionary approach; Hydraulic engineering; Roughness coefficient; Roughness coefficient estimations, Rivers},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baia2021552,
author = {Baia, A.E. and Di Bari, G. and Poggioni, V.},
title = {Effective Universal Unrestricted Adversarial Attacks Using a MOE Approach},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2021},
volume = {12694 LNCS},
pages = {552-567},
doi = {10.1007/978-3-030-72699-7_35},
note = {Conference of 24th International Conference on the Applications of Evolutionary Computation, EvoApplications 2021 held as Part of EvoStar 2021 ; Conference Date: 7 April 2021 Through 9 April 2021; Conference Code:257359},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107477969&doi=10.1007%2f978-3-030-72699-7_35&partnerID=40&md5=c63ae770605e1bafd5c185425cf0acc0},
abstract = {Recent studies have shown that Deep Leaning models are susceptible to adversarial examples, which are data, in general images, intentionally modified to fool a machine learning classifier. In this paper, we present a multi-objective nested evolutionary algorithm to generate universal unrestricted adversarial examples in a black-box scenario. The unrestricted attacks are performed through the application of well-known image filters that are available in several image processing libraries, modern cameras, and mobile applications. The multi-objective optimization takes into account not only the attack success rate but also the detection rate. Experimental results showed that this approach is able to create a sequence of filters capable of generating very effective and undetectable attacks. © 2021, Springer Nature Switzerland AG.},
author_keywords = {Deep learning; Evolutionary algorithms; Multi-objective optimization; Universal adversarial attacks},
keywords = {Image processing; Learning systems; Multiobjective optimization; Turing machines, Black boxes; Detection rates; Image filters; Image processing libraries; Mobile applications; Multi objective, Evolutionary algorithms},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti20211,
author = {Baioletti, M. and Rasconi, R. and Oddi, A.},
title = {A Novel Ant Colony Optimization Strategy for the Quantum Circuit Compilation Problem},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2021},
volume = {12692 LNCS},
pages = {1-16},
doi = {10.1007/978-3-030-72904-2_1},
note = {Conference of 21st European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2021 Held as Part of EvoStar 2021 ; Conference Date: 7 April 2021 Through 9 April 2021; Conference Code:256999},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85107373623&doi=10.1007%2f978-3-030-72904-2_1&partnerID=40&md5=535d412b18f0dd9b1990c63668514322},
abstract = {Quantum Computing represents the most promising technology towards speed boost in computation, opening the possibility of major breakthroughs in several disciplines including Artificial Intelligence. This paper investigates the performance of a novel Ant Colony Optimization (ACO) algorithm for the realization (compilation) of nearest-neighbor compliant quantum circuits of minimum duration. In fact, current technological limitations (e.g., decoherence effect) impose that the overall duration (makespan) of the quantum circuit realization be minimized, and therefore the production of minimum-makespan compiled circuits for present and future quantum machines is of paramount importance. In our ACO algorithm (QCC-ACO), we introduce a novel pheromone model, and we leverage a heuristic-based Priority Rule to control the iterative selection of the quantum gates to be inserted in the solution. The proposed QCC-ACO algorithm has been tested on a set of quantum circuit benchmark instances of increasing sizes available from the recent literature. We demonstrate that the QCC-ACO obtains results that outperform the current best solutions in the literature against the same benchmark, succeeding in significantly improving the makespan values for a great number of instances and demonstrating the scalability of the approach. © 2021, Springer Nature Switzerland AG.},
author_keywords = {Ant Colony Optimization; Planning; Quantum circuit compilation; Scheduling},
keywords = {Artificial intelligence; Benchmarking; Combinatorial optimization; Evolutionary algorithms; Iterative methods; Quantum computers; Quantum theory; Timing circuits, Ant Colony Optimization algorithms; Ant colony optimization strategy; Compilation problems; Decoherence effects; Nearest neighbors; Quantum Computing; Quantum machines; Technological limitations, Ant colony optimization},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Tracolli20201499,
author = {Tracolli, M. and Baioletti, M. and Poggioni, V. and Spiga, D.},
title = {Effective Big Data Caching through Reinforcement Learning},
journal = {Proceedings - 19th IEEE International Conference on Machine Learning and Applications, ICMLA 2020},
year = {2020},
pages = {1499-1504},
doi = {10.1109/ICMLA51294.2020.00231},
art_number = {9356236},
note = {Conference of 19th IEEE International Conference on Machine Learning and Applications, ICMLA 2020 ; Conference Date: 14 December 2020 Through 17 December 2020; Conference Code:167387},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85102529387&doi=10.1109%2fICMLA51294.2020.00231&partnerID=40&md5=75819d82d9dce831bd8c79826f146579},
abstract = {In the era of big data, data volumes continue to grow in several different domains, from business to scientific fields. Sensors, edge devices, scientific applications and detectors generate huge amounts of data that are distributed for their nature. In order to extract value from such data requires a typical pipeline made of two main steps: first, the processing and then the data access. One of the main features for data access is fast response time, whose order of magnitude can vary a lot depending on the specific type of processing as well as processing patterns. The optimization of the access layer becomes more and more important while dealing with a geographically distributed environment where data must be retrieved from remote servers of a data lake. From the infrastructural perspectives, caching systems are used to mitigate latency and to serve better popular data. Thus, the role of the cache becomes a key to have an effective and efficient data access. In this article, we propose a Reinforcement Learning approach, using the Q-Learning technique, to improve the performances of a cache system in terms of data management. The proposed method uses two agents with different objectives and actions to control the addition and the eviction of files in the cache. The aim of this system is to increase the throughput reducing, at the same time, the cache costs, such as the amount of data written, and network utilization. Moreover, we tested our method in a context of data analysis, with information taken from High Energy Physics (HEP) workflow. © 2020 IEEE.},
author_keywords = {addition policy; big data; cache; data science workflow; eviction policy; intelligent system; optimization; reinforcement learning},
keywords = {Big data; High energy physics; Learning systems; Pipeline processing systems; Reinforcement learning, Different domains; Distributed environments; Fast response time; Net work utilization; Reinforcement learning approach; Remote servers; Scientific applications; Scientific fields, Information management},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni202036063,
author = {Franzoni, V. and Biondi, G. and Milani, A.},
title = {Emotional sounds of crowds: spectrogram-based analysis using deep learning},
journal = {Multimedia Tools and Applications},
year = {2020},
volume = {79},
number = {47-48},
pages = {36063-36075},
doi = {10.1007/s11042-020-09428-x},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089457887&doi=10.1007%2fs11042-020-09428-x&partnerID=40&md5=7af5f7ac3a9d077756cc478fe9a89944},
abstract = {Crowds express emotions as a collective individual, which is evident from the sounds that a crowd produces in particular events, e.g., collective booing, laughing or cheering in sports matches, movies, theaters, concerts, political demonstrations, and riots. A critical question concerning the innovative concept of crowd emotions is whether the emotional content of crowd sounds can be characterized by frequency-amplitude features, using analysis techniques similar to those applied on individual voices, where deep learning classification is applied to spectrogram images derived by sound transformations. In this work, we present a technique based on the generation of sound spectrograms from fragments of fixed length, extracted from original audio clips recorded in high-attendance events, where the crowd acts as a collective individual. Transfer learning techniques are used on a convolutional neural network, pre-trained on low-level features using the well-known ImageNet extensive dataset of visual knowledge. The original sound clips are filtered and normalized in amplitude for a correct spectrogram generation, on which we fine-tune the domain-specific features. Experiments held on the finally trained Convolutional Neural Network show promising performances of the proposed model to classify the emotions of the crowd. © 2020, The Author(s).},
author_keywords = {CNN; Crowd computing; Crowd emotions; Emotion recognition; Image recognition; Transfer learning},
keywords = {Audio acoustics; Convolution; Convolutional neural networks; Spectrographs; Transfer learning, Analysis techniques; Critical questions; Domain specific; Express emotions; Learning techniques; Low-level features; Sound transformations; Visual knowledge, Deep learning},
publisher = {Springer},
document_type = {Article},
source = {Scopus}
}
@article{Biondi20201,
author = {Biondi, G. and Franzoni, V.},
title = {Discovering correlation indices for link prediction using differential evolution},
journal = {Mathematics},
year = {2020},
volume = {8},
number = {11},
pages = {1-10},
doi = {10.3390/math8112097},
art_number = {2097},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096463120&doi=10.3390%2fmath8112097&partnerID=40&md5=e6f347fc01a286a561961d0fae31aabc},
abstract = {Binary correlation indices are crucial for forecasting and modelling tasks in different areas of scientific research. The setting of sound binary correlations and similarity measures is a long and mostly empirical interactive process, in which researchers start from experimental correlations in one domain, which usually prove to be effective in other similar fields, and then progressively evaluate and modify those correlations to adapt their predictive power to the specific characteristics of the domain under examination. In the research of prediction of links on complex networks, it has been found that no single correlation index can always obtain excellent results, even in similar domains. The research of domain-specific correlation indices or the adaptation of known ones is therefore a problem of critical concern. This paper presents a solution to the problem of setting new binary correlation indices that achieve efficient performances on specific network domains. The proposed solution is based on Differential Evolution, evolving the coefficient vectors of meta-correlations, structures that describe classes of binary similarity indices and subsume the most known correlation indices for link prediction. Experiments show that the proposed evolutionary approach always results in improved performances, and in some cases significantly enhanced, compared to the best correlation indices available in the link prediction literature, effectively exploring the correlation space and exploiting its self-adaptability to the given domain to improve over generations. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
author_keywords = {Binary correlation; Evolutionary algorithms; Evolutionary optimisation; Similarity of structure; Topological similarity},
publisher = {MDPI AG},
document_type = {Article},
source = {Scopus}
}
@article{vanderGaag2020272,
author = {van der Gaag, L.C. and Baioletti, M. and Bolt, J.H.},
title = {A lattice-based representation of independence relations for efficient closure computation},
journal = {International Journal of Approximate Reasoning},
year = {2020},
volume = {126},
pages = {272-289},
doi = {10.1016/j.ijar.2020.08.002},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090601580&doi=10.1016%2fj.ijar.2020.08.002&partnerID=40&md5=5bc573792c8d41027d16a477693ca2e2},
abstract = {Independence relations in general include exponentially many statements of independence, that is, exponential in the number of variables involved. These relations are typically characterised however, by a small set of such statements and an associated set of derivation rules. While various computational problems on independence relations can be solved by manipulating these smaller sets without the need to explicitly generate the full relation, existing algorithms for constructing these sets are associated with often prohibitively high running times. In this paper, we introduce a lattice structure for organising sets of independence statements and show that current algorithms are rendered computationally less demanding by exploiting new insights in the structural properties of independence gained from this lattice organisation. By means of a range of experimental results, we subsequently demonstrate that through the lattice organisation indeed a substantial gain in efficiency is achieved for fast-closure computation of semi-graphoid independence relations in practice. © 2020},
author_keywords = {Algorithm engineering; Fast-closure computation; Independence relations; Lattice-based partitioning; Representation},
keywords = {Structural properties, Associated sets; Closure computations; Computational problem; Derivation rules; Lattice structures; Lattice-based; Running time, Computational efficiency},
publisher = {Elsevier Inc.},
document_type = {Article},
source = {Scopus}
}
@article{Franzoni202011,
author = {Franzoni, V. and Milani, A. and Mengoni, P. and Piccinato, F.},
title = {Artificial intelligence visual metaphors in e-learning interfaces for learning analytics},
journal = {Applied Sciences (Switzerland)},
year = {2020},
volume = {10},
number = {20},
pages = {1-25},
doi = {10.3390/app10207195},
art_number = {7195},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092781596&doi=10.3390%2fapp10207195&partnerID=40&md5=ca128efbb6f09648608249a2c98312cc},
abstract = {This work proposes an innovative visual tool for real-time continuous learners analytics. The purpose of the work is to improve the design, functionality, and usability of learning management systems to monitor user activity to allow educators to make informed decisions on e-learning design, usually limited to dashboards graphs, tables, and low-usability user logs. The standard visualisation is currently scarce, and often inadequate to inform educators about the design quality and students engagement on their learning objects. The same low usability can be found in learning analytics tools, which mostly focus on post-course analysis, demanding specific skills to be effectively used, e.g., for statistical analysis and database queries. We propose a tool for student analytics embedded in a Learning Management System, based on the innovative visual metaphor of interface morphing. Artificial intelligence provides in remote learning immediate feedback, crucial in a face-to-face setting, highlighting the students’ engagement in each single learning object. A visual metaphor is the representation of a person, group, learning object, or concept through a visual image that suggests a particular association or point of similarity. The basic idea is that elements of the application interface, e.g., learning objects’ icons and student avatars, can be modified in colour and dimension to reflect key performance indicators of learner’s activities. The goal is to provide high-affordance information on the student engagement and usage of learning objects, where aggregation functions on subsets of users allow a dynamic evaluation of cohorts with different granularity. The proposed visual metaphors (i.e., thermometer bar, dimensional morphing, and tag cloud morphing) have been implemented and experimented within academic-level courses. Experimental results have been evaluated with a comparative analysis of user logs and a subjective usability survey, which show that the tool obtains quantitative, measurable effectiveness and the qualitative appreciation of educators. Among metaphors, the highest success is obtained by Dimensional morphing and Tag cloud transformation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
author_keywords = {Arttificial Intelligence–based visual interface; Course evaluation; Information visualization; Learner continuous monitoring; Teachers self-evaluation; Usability},
publisher = {MDPI AG},
document_type = {Article},
source = {Scopus}
}
@article{Milani20201,
author = {Milani, A.},
title = {Evolutionary algorithms in intelligent systems},
journal = {Mathematics},
year = {2020},
volume = {8},
number = {10},
pages = {1-2},
doi = {10.3390/math8101733},
art_number = {1733},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092905686&doi=10.3390%2fmath8101733&partnerID=40&md5=6e22ece896d6f97bb6035e4cd68eea14},
publisher = {MDPI AG},
document_type = {Editorial},
source = {Scopus}
}
@article{Franzoni202012,
author = {Franzoni, V. and Biondi, G. and Perri, D. and Gervasi, O.},
title = {Enhancing mouth-based emotion recognition using transfer learning},
journal = {Sensors (Switzerland)},
year = {2020},
volume = {20},
number = {18},
pages = {1-15},
doi = {10.3390/s20185222},
art_number = {5222},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85090766688&doi=10.3390%2fs20185222&partnerID=40&md5=8cdec70452e71333af51ae7dffe77c15},
abstract = {This work concludes the first study on mouth-based emotion recognition while adopting a transfer learning approach. Transfer learning results are paramount for mouth-based emotion emotion recognition, because few datasets are available, and most of them include emotional expressions simulated by actors, instead of adopting real-world categorisation. Using transfer learning, we can use fewer training data than training a whole network from scratch, and thus more efficiently fine-tune the network with emotional data and improve the convolutional neural network’s performance accuracy in the desired domain. The proposed approach aims at improving emotion recognition dynamically, taking into account not only new scenarios but also modified situations to the initial training phase, because the image of the mouth can be available even when the whole face is visible only in an unfavourable perspective. Typical applications include automated supervision of bedridden critical patients in a healthcare management environment, and portable applications supporting disabled users having difficulties in seeing or recognising facial emotions. This achievement takes advantage of previous preliminary works on mouth-based emotion recognition using deep-learning, and has the further benefit of having been tested and compared to a set of other networks using an extensive dataset for face-based emotion recognition, well known in the literature. The accuracy of mouth-based emotion recognition was also compared to the corresponding full-face emotion recognition; we found that the loss in accuracy is mostly compensated by consistent performance in the visual emotion recognition domain. We can, therefore, state that our method proves the importance of mouth detection in the complex process of emotion recognition. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
author_keywords = {Convolutional neural networks; Emotion recognition; Transfer learning},
keywords = {Convolutional neural networks; Deep learning; Image enhancement; Speech recognition; Transfer learning, Complex Processes; Consistent performance; Emotion recognition; Emotional expressions; Facial emotions; Health-care managements; Portable applications; Typical application, Face recognition, emotion; face; human; learning; machine learning; mouth, Emotions; Face; Humans; Learning; Machine Learning; Mouth},
publisher = {MDPI AG},
document_type = {Article},
source = {Scopus}
}
@article{Mengoni2020904,
author = {Mengoni, P. and Milani, A. and Poggioni, V. and Li, Y.},
title = {Community elicitation from co-occurrence of activities},
journal = {Future Generation Computer Systems},
year = {2020},
volume = {110},
pages = {904-917},
doi = {10.1016/j.future.2019.10.046},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075426622&doi=10.1016%2fj.future.2019.10.046&partnerID=40&md5=76cac2ceca5a62c5b5f7e16fa4cb4e17},
abstract = {With reference only to observations of people's activities within a system, we investigated whether it is possible to determine the existence of their social relationships. As students interacted, either individually or in groups, we aimed to discover their social communities given the temporal and spatial co-occurrence of their activities and their implicit user–system interactions. To elicit those hidden communities, we developed two innovative approaches: history-based analysis, which exploits the similarity of users’ histories of engaging in certain activities, and session-based analysis, which uses a graph-based representation of concurrent users’ activity sessions. We tested and validated both approaches using a real-world dataset representing the activity logs of students using a virtual learning environment platform. The major results of our work confirm that the co-occurrence of people's activities is an emerging epiphenomenon of hidden, implicit exchanges of information in side-channel communications. © 2019 Elsevier B.V.},
author_keywords = {Community detection; Graph analysis; Graph modelling; Learning analytics; Modularity; Similarity measures; Social networks},
keywords = {Graphic methods; Social networking (online), Community detection; Graph analysis; Learning analytics; Modularity; Similarity measure, Computer aided instruction},
publisher = {Elsevier B.V.},
document_type = {Article},
source = {Scopus}
}
@conference{Santucci20201704,
author = {Santucci, V. and Ceberio, J. and Baioletti, M.},
title = {Gradient search in the space of permutations: An application for the linear ordering problem},
journal = {GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion},
year = {2020},
pages = {1704-1711},
doi = {10.1145/3377929.3398094},
note = {Conference of 2020 Genetic and Evolutionary Computation Conference, GECCO 2020 ; Conference Date: 8 July 2020 Through 12 July 2020; Conference Code:161684},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089755761&doi=10.1145%2f3377929.3398094&partnerID=40&md5=687793ec478218031216f04dfb702e5c},
abstract = {Gradient search is a classical technique for optimizing differentiable functions that has gained much relevance recently due to its application on Neural Network training. Despite its popularity, the application of gradient search has been limited to the continuous optimization and its usage in the combinatorial case is confined to a few works, all which tackle the binary search space. In this paper, we present a new approach for applying Gradient Search to the space of permutations. The idea consists of optimizing the expected objective value of a random variable defined over permutations. Such a random variable is distributed according to the Plackett-Luce model, and a gradient search over its continuous parameters is performed. Conducted experiments on a benchmark of the linear ordering problem confirm that the Gradient Search performs better than its counterpart Estimation of Distribution Algorithm: the Plackett-Luce EDA. Moreover, results reveal that the scalability of the Gradient Search is better than that of the PL-EDA. © 2020 ACM.},
author_keywords = {Gradient search; Optimization; Permutations; Symmetric group},
keywords = {Optimization; Random variables, Classical techniques; Continuous optimization; Continuous parameters; Differentiable functions; Estimation of distribution algorithms; ITS applications; Linear ordering problems; Neural network training, Set theory},
sponsors = {ACM SIGEVO},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{DIBari20201678,
author = {DI Bari, G. and Baioletti, M. and Santucci, V.},
title = {An experimental evaluation of the algebraic differential evolution algorithm on the single row facility layout problem},
journal = {GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion},
year = {2020},
pages = {1678-1684},
doi = {10.1145/3377929.3398130},
note = {Conference of 2020 Genetic and Evolutionary Computation Conference, GECCO 2020 ; Conference Date: 8 July 2020 Through 12 July 2020; Conference Code:161684},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089726628&doi=10.1145%2f3377929.3398130&partnerID=40&md5=822c179f2be4ca31c12f31833eff78de},
abstract = {The Algebraic Differential Evolution for Permutations (ADEP) has been recently proposed as an effective evolutionary algorithm for permutation-based optimization problems. ADEP is built upon a framework that exploits the rich algebraic structure of the permutations search space. In this paper we further explore the abilities of ADEP by presenting an implementation for the Single Row Facility Layout Problem (SRFLP): a permutation problem with interesting real-world applications ranging from designing the layouts of machines in certain manufacturing systems to optimally arranging rooms in hospitals. An experimental investigation was conducted on a set of commonly adopted benchmarks and different settings ADEP were compared among them and with respect to the other methods in the literature. Interestingly, the experimental results confirm the validity of ADEP by showing its competitiveness with respect to the state-of-the-art results for the SRFLP. © 2020 ACM.},
author_keywords = {Algebraic differential evolution; Combinatorial optimization; Differential evolution},
keywords = {Algebra; Manufacture; Optimization; Plant layout, Algebraic structures; Differential Evolution; Differential evolution algorithms; Experimental evaluation; Experimental investigations; Facility layout problems; Optimization problems; Permutation problems, Evolutionary algorithms},
sponsors = {ACM SIGEVO},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti20201824,
author = {Baioletti, M. and Coello, C.A.C. and DI Bari, G. and Poggioni, V.},
title = {Multi-objective evolutionary GAN},
journal = {GECCO 2020 Companion - Proceedings of the 2020 Genetic and Evolutionary Computation Conference Companion},
year = {2020},
pages = {1824-1831},
doi = {10.1145/3377929.3398138},
note = {Conference of 2020 Genetic and Evolutionary Computation Conference, GECCO 2020 ; Conference Date: 8 July 2020 Through 12 July 2020; Conference Code:161684},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85089726188&doi=10.1145%2f3377929.3398138&partnerID=40&md5=df7f6f3ad3cef0f26f063567f3578490},
abstract = {Generative Adversarial Network (GAN) is a generative model proposed to imitate real data distributions. The original GAN algorithm has been found to be able to achieve excellent results for the image generation task, but it suffers from problems such as instability and mode collapse. To tackle these problems, many variants of the original model have been proposed; one of them is the Evolutionary GAN (EGAN), where a population of generators is evolved. Inspired by EGAN, we propose here a new algorithm, called Multi-Objective Evolutionary Generative Adversarial Network (MOEGAN), which reformulates the problem of training GANs as a multi-objective optimization problem. Thus, Pareto dominance is used to select the best solutions, evaluated using diversity and quality fitness functions. Preliminary experimental results on synthetic datasets show how the proposed approach can achieve better results than EGAN. © 2020 ACM.},
author_keywords = {Deep generative models; Evolutionary algorithms; General adversarial network; Multi objective},
keywords = {Multiobjective optimization, Adversarial networks; Data distribution; Fitness functions; Generative model; Image generations; Multi-objective evolutionary; Multi-objective optimization problem; Synthetic datasets, Evolutionary algorithms},
sponsors = {ACM SIGEVO},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Santucci2020,
author = {Santucci, V. and Baioletti, M. and Milani, A.},
title = {An algebraic framework for swarm and evolutionary algorithms in combinatorial optimization},
journal = {Swarm and Evolutionary Computation},
year = {2020},
volume = {55},
doi = {10.1016/j.swevo.2020.100673},
art_number = {100673},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85081117315&doi=10.1016%2fj.swevo.2020.100673&partnerID=40&md5=e2dd9398c0b12b72653a272493ef89e3},
abstract = {A popular trend in evolutionary computation is to adapt numerical algorithms to combinatorial optimization problems. For instance, this is the case of a variety of Particle Swarm Optimization and Differential Evolution implementations for both binary and permutation-based optimization problems. In this paper, after highlighting the main drawbacks of the approaches in literature, we provide an algebraic framework which allows to derive fully discrete variants of a large class of numerical evolutionary algorithms to tackle many combinatorial problems. The strong mathematical foundations upon which the framework is built allow to redefine numerical evolutionary operators in such a way that their original movements in the continuous space are simulated in the discrete space. Algebraic implementations of Differential Evolution and Particle Swarm Optimization are then proposed. Experiments have been held to compare the algebraic algorithms to the most popular schemes in literature and to the state-of-the-art results for the tackled problems. Experimental results clearly show that algebraic algorithms outperform the competitors and are competitive with the state-of-the-art results. © 2020 Elsevier B.V.},
author_keywords = {Algebraic evolutionary algorithms; Algebraic evolutionary computation; Combinatorial search spaces},
keywords = {Algebra; Combinatorial optimization; Mathematical operators; Particle swarm optimization (PSO), Combinatorial optimization problems; Combinatorial problem; Combinatorial search; Differential Evolution; Differential evolution and particle swarm optimizations; Evolutionary operators; Mathematical foundations; Optimization problems, Combinatorial mathematics},
publisher = {Elsevier B.V.},
document_type = {Article},
source = {Scopus}
}
@article{Tracolli2020650,
author = {Tracolli, M. and Baioletti, M. and Poggioni, V. and Spiga, D. and on behalf of the CMS Collaboration},
title = {Caching Suggestions Using Reinforcement Learning},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12565 LNCS},
pages = {650-662},
doi = {10.1007/978-3-030-64583-0_57},
note = {Conference of 6th International Conference on Machine Learning, Optimization, and Data Science, LOD 2020 ; Conference Date: 19 July 2020 Through 23 July 2020; Conference Code:253909},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85101226578&doi=10.1007%2f978-3-030-64583-0_57&partnerID=40&md5=6481e94ac39115672f423b082611209a},
abstract = {Big data is usually processed in a decentralized computational environment with a number of distributed storage systems and processing facilities to enable both online and offline data analysis. In such a context, data access is fundamental to enhance processing efficiency as well as the user experience inspecting the data and the caching system is a solution widely adopted in many diverse domains. In this context, the optimization of cache management plays a central role to sustain the growing demand for data. In this article, we propose an autonomous approach based on a Reinforcement Learning technique to implement an agent to manage the file storing decisions. Moreover, we test the proposed method in a real context using the information on data analysis workflows of the CMS experiment at CERN. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Addition policy; Big data; Cache; Data science workflow; Intelligent system; Optimization; Reinforcement learning},
keywords = {Data handling; Data Science; Digital storage; Learning systems; Multiprocessing systems; Online systems; User experience, Cache management; Caching system; Computational environments; Distributed storage system; Diverse domains; Growing demand; Processing facilities; Reinforcement learning techniques, Reinforcement learning},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Tracolli2020320,
author = {Tracolli, M. and Baioletti, M. and Ciangottini, D. and Poggioni, V. and Spiga, D.},
title = {An Intelligent Cache Management for Data Analysis at CMS},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12250 LNCS},
pages = {320-332},
doi = {10.1007/978-3-030-58802-1_24},
note = {Conference of 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference Date: 1 July 2020 Through 4 July 2020; Conference Code:249529},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093116556&doi=10.1007%2f978-3-030-58802-1_24&partnerID=40&md5=d34ac09584b988e21c02383a1084c3ce},
abstract = {In this work, we explore a score-based approach to manage a cache system. With the proposed method, the cache can better discriminate the input requests and improve the overall performances. We created a score based discriminator using the file statistics. The score represents the weight of a file. We tested several functions to compute the file weight used to determine whether a file has to be stored in the cache or not. We developed a solution experimenting on a real cache manager named XCache, that is used within the Compact Muon Solenoid (CMS) data analysis workflow. The aim of this work is optimizing to reduce maintaining costs of the cache system without compromising the user experience. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Big data; Cache; Data science workflow; Intelligent system; LRU; Optimization},
keywords = {Data handling; Information analysis; User experience, Analysis workflow; Cache management; Cache manager; Cache systems; Compact Muon solenoids, Solenoids},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2020562,
author = {Franzoni, V. and Biondi, G. and Milani, A.},
title = {Exploring Negative Emotions to Preserve Social Distance in a Pandemic Emergency},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12250 LNCS},
pages = {562-573},
doi = {10.1007/978-3-030-58802-1_40},
note = {Conference of 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference Date: 1 July 2020 Through 4 July 2020; Conference Code:249529},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093087464&doi=10.1007%2f978-3-030-58802-1_40&partnerID=40&md5=d236e4c98c1c90d9033659c35e650f8b},
abstract = {In this work, we present a multi-agent robotic system which explores the use of unpleasant emotions triggered by visual, sound and behavioural affordances of autonomous agents to interact with humans for preserving social distance in public spaces in a context of a pandemic emergency. The idea was born in the context of the Covid-19 pandemic, where discomfort and fear have been widely used by governments to preserve social distancing. This work does not implicitly endorse the use of fear to keep order but explores controlled and moderate automated exploitations. On the contrary, it deeply analyses the pros and cons of the ethical use of robots with emotion recognition and triggering capabilities. The system employs a swarm of all-terrain hexapods patrolling a public open space and generally having a discrete and seamless presence. The goal is to preserve the social distance among the public with effective but minimal intervention, limited to anomaly detection. The single agents implement critical tasks: context detection strategies, triggering negative emotions at different degrees of arousal using affordances ranging from appearance and simple proximity or movements to disturbing sounds or explicit voice messages. The whole system exhibits an emerging swarm behaviour where the agents cooperate and coordinate in a distributed way, adapting and reacting to the context. An innovative contribution of this work, more than the application, is the use of unpleasant emotions affordances in an ethical way, to attract user attention and induce the desired behaviour in the emergency. This work also introduces a method for assessment of the emotional level of individuals and groups of people in the context of swarm agents. The system extends the experience of the gAItano hexapod project, an autonomous agent with image detection and planned object relocation capabilities. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Affective computing; Autonomous agents; COVID; Emotion affordance; Social distance; Swarm behaviour},
keywords = {Anomaly detection; Multi agent systems; Object detection; Philosophical aspects; Social robots; Speech recognition, Context detection; Critical tasks; Emotion recognition; Image detection; Multi-agent robotic systems; Public open spaces; Social distance; User attention, Autonomous agents},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2020293,
author = {Franzoni, V. and Pallottelli, S. and Milani, A.},
title = {Reshaping Higher Education with e-Studium, a 10-Years Capstone in Academic Computing},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12250 LNCS},
pages = {293-303},
doi = {10.1007/978-3-030-58802-1_22},
note = {Conference of 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference Date: 1 July 2020 Through 4 July 2020; Conference Code:249529},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85093083088&doi=10.1007%2f978-3-030-58802-1_22&partnerID=40&md5=d635736d554b4e972bcb2fce7ef7941b},
abstract = {E-Studium has been a long-running project of blended e-learning for higher education based on the learning management system Moodle, implemented at University of Perugia, Italy from 2005 to 2015. The capstone culminated in a refined final product, at the basis of the actual academic platform Unistudium. In its ten-years activity, e-Studium has been a learning pathway experience for a variety of applications, included STEM courses, from high school education to high-specialisation academic courses, teacher’s qualification, and third mission for technology transfer, with a particular focus on usability and teacher’s self-evaluation. The analysis of both objective and subjective evaluations, collected over ten years from activity logs, web analytics, global rankings, and ad hoc questionnaires, together with teachers and students’ outcomes, shows how e-Studium contributed to reshaping the educational offer of large-scale learning in University of Perugia and Italy. This paper aims at showing the evolution and the outcomes of e-Studium, under the vision of the contemporary natural evolution of the technological learning economy, assessing and sharing educational experiences based on the evolution of innovative technologies for lifelong e-learning. A particular focus will be given on how such contribution can enhance the actual extraordinary situation, which sees a worldwide unexpected and abrupt need for remote communication due to the COVID-19 emergency. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Academic freedom; Continuous education; Coronavirus; ICT; Institutional diversity; STEM},
keywords = {E-learning; Surveys; Teaching; Technology transfer, Blended e-learning; Educational experiences; Innovative technology; Large-scale learning; Learning management system; Objective and subjective evaluations; Remote communication; Technological learning, Engineering education},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Biondi2020132,
author = {Biondi, G. and Franzoni, V.},
title = {Semantic Similarity Measures for Topological Link Prediction},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12253 LNCS},
pages = {132-142},
doi = {10.1007/978-3-030-58814-4_10},
note = {Conference of 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference Date: 1 July 2020 Through 4 July 2020; Conference Code:249529},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092899533&doi=10.1007%2f978-3-030-58814-4_10&partnerID=40&md5=92c19332ae45b206a5f1dcb1bc045da7},
abstract = {The semantic approach to data linked in social networks uses information extracted from node attributes to quantify the similarity between nodes. In contrast, the topological approach exploits the structural information of the network, e.g., nodes degree, paths, neighbourhood breadth. For a long time, such approaches have been considered substantially separated. In recent years, following the widespread of social media, an increasing focus has been dedicated to understanding how complex networks develop, following the human phenomena they represent, considering both the meaning of the node and the links structure and distribution. The link prediction problem, aiming at predicting how networks evolve in terms of connections between entities, is suitable to apply semantic similarity measures to a topological domain. In this paper, we introduce a novel topological formulation of semantic measures, e.g., NGD, PMI, Confidence, in a unifying framework for link prediction in social graphs, providing results of systematic experiments. We validate the approach discussing the prediction capability on widely accepted data sets, comparing the performance of the topological formulation of semantic measures to the conventional metrics generally used in literature. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Complex networks; Graph-based link prediction; Ranking-based approach; Structural link prediction; Unified view},
keywords = {Complex networks; Forecasting; Semantics, Link prediction; Prediction capability; Semantic approach; Semantic measures; Semantic similarity measures; Structural information; Systematic experiment; Topological approach, Topology},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Niyogi202093,
author = {Niyogi, R. and Sharma, S. and Vavrecka, M. and Milani, A.},
title = {A Learning Based Approach for Planning with Safe Actions},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12253 LNCS},
pages = {93-105},
doi = {10.1007/978-3-030-58814-4_7},
note = {Conference of 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference Date: 1 July 2020 Through 4 July 2020; Conference Code:249529},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092896851&doi=10.1007%2f978-3-030-58814-4_7&partnerID=40&md5=01d66c93ab074e92e4e5e5fb6d462434},
abstract = {Given a configuration involving some objects in an environment, the planning problem, considered in this paper, is to find a plan that rearranges these objects so as to place a new object. The challenging aspect here involves deciding when an object can be placed on top of another object. Here only defining standard planning operators would not suffice. For instance, using these operators we can come up with actions that may be performed at a state but it should not be performed. So we introduce the notion of safe actions whose outcomes are consistent with the laws of physics, commonsense, and common practice. A safe action can be performed if a robot performing the action knows the knowledge of the situation. We developed a knowledge engine using a supervised learning technique. However, unlike the common task of learning functions, our approach is to learn predicates–that evaluate to binary values. By learning such a predicate a robot would be able to decide whether or not an object A can be placed on top of another object B. We give a method to handle new objects for which the predicates have not been learned. We suggest a nondeterministic planning algorithm to synthesize plans that contain only safe actions. Experimental results show the efficacy of our approach. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Learning; Planning; Predicate; Safe actions},
keywords = {Robots; Supervised learning, Binary values; Knowledge Engines; Laws of physics; Learning functions; Learning-based approach; Nondeterministic planning; Planning operators; Planning problem, Learning systems},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Santucci2020367,
author = {Santucci, V. and Forti, L. and Santarelli, F. and Spina, S. and Milani, A.},
title = {Learning to Classify Text Complexity for the Italian Language Using Support Vector Machines},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12250 LNCS},
pages = {367-376},
doi = {10.1007/978-3-030-58802-1_27},
note = {Conference of 20th International Conference on Computational Science and Its Applications, ICCSA 2020 ; Conference Date: 1 July 2020 Through 4 July 2020; Conference Code:249529},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092771548&doi=10.1007%2f978-3-030-58802-1_27&partnerID=40&md5=e818b30c107dd99b2d473f5aa266697e},
abstract = {Natural language processing is undoubtedly one of the most active fields of research in the machine learning community. In this work we propose a supervised classification system that, given in input a text written in the Italian language, predicts its linguistic complexity in terms of a level of the Common European Framework of Reference for Languages (better known as CEFR). The system was built by considering: (i) a dataset of texts labeled by linguistic experts was collected, (ii) some vectorisation procedures which transform any text to a numerical representation, and (iii) the training of a support vector machine’s model. Experiments were conducted following a statistically sound design and the experimental results show that the system is able to reach a good prediction accuracy. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Natural Language Processing; Support vector machines; Text classification},
keywords = {Classification (of information); Linguistics; Natural language processing systems; Support vector machines; Text processing, Linguistic complexity; Machine learning communities; NAtural language processing; Numerical representation; Prediction accuracy; Sound designs; Supervised classification; Vectorisation, Learning systems},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2020201,
author = {Baioletti, M. and Di Bari, G. and Milani, A. and Santucci, V.},
title = {An experimental comparison of algebraic crossover operators for permutation problems},
journal = {Fundamenta Informaticae},
year = {2020},
volume = {174},
number = {3-4},
pages = {201-228},
doi = {10.3233/FI-2020-1940},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85092602601&doi=10.3233%2fFI-2020-1940&partnerID=40&md5=8a709698da371934da04c439322bd4fc},
abstract = {Crossover operators are very important components in Evolutionary Computation. Here we are interested in crossovers for the permutation representation that find applications in combinatorial optimization problems such as the permutation flowshop scheduling and the traveling salesman problem. We introduce three families of permutation crossovers based on algebraic properties of the permutation space. In particular, we exploit the group and lattice structures of the space. A total of 34 new crossovers is provided. Algebraic and semantic properties of the operators are discussed, while their performances are investigated by experimentally comparing them with known permutation crossovers on standard benchmarks from four popular permutation problems. Three different experimental scenarios are considered and the results clearly validate our proposals. © 2020 BMJ Publishing Group. All rights reserved.},
author_keywords = {Algebraic crossovers; Lattice operators; Permutation crossovers},
keywords = {Algebra; Combinatorial optimization; Semantics, Algebraic properties; Combinatorial optimization problems; Experimental comparison; Lattice structures; Permutation flow-shop scheduling; Permutation problems; Permutation representation; Semantic properties, Traveling salesman problem},
publisher = {IOS Press BV},
document_type = {Article},
source = {Scopus}
}
@article{Santucci202038,
author = {Santucci, V. and Baioletti, M.},
title = {A memetic approach for the orienteering problem},
journal = {Communications in Computer and Information Science},
year = {2020},
volume = {1200 CCIS},
pages = {38-48},
doi = {10.1007/978-3-030-45016-8_5},
note = {Conference of 14th International Workshop on Artificial Life and Evolutionary Computation, WIVACE 2019 ; Conference Date: 18 September 2019 Through 20 September 2019; Conference Code:242369},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088754119&doi=10.1007%2f978-3-030-45016-8_5&partnerID=40&md5=76da27508d977817f555c1825f244e1a},
abstract = {In this paper we present a new memetic approach to solve the orienteering problem. The key method of our proposal is the procedure ReduceExtend which, starting from a permutation of all the vertices in the orienteering problem, produces a feasible path with a locally optimal score. This procedure is coupled with an evolutionary algorithm which navigate the search space of permutations. In our experiments we have considered the following algorithms: the algebraic differential evolution algorithm, and the three continuous algorithms CMA-ES, DE and PSO equipped with the random key technique. The experimental results show that the proposed approach is competitive with the state of the art results of some selected benchmark instances. © Springer Nature Switzerland AG 2020.},
keywords = {Artificial life; Benchmarking; Optimization, Continuous algorithms; Differential evolution algorithms; Memetic approach; Orienteering problem; Random keys; Search spaces; State of the art, Evolutionary algorithms},
publisher = {Springer},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti202090,
author = {Baioletti, M. and Di Bari, G. and Poggioni, V.},
title = {An analysis of cooperative coevolutionary differential evolution as neural networks optimizer},
journal = {Communications in Computer and Information Science},
year = {2020},
volume = {1200 CCIS},
pages = {90-99},
doi = {10.1007/978-3-030-45016-8_10},
note = {Conference of 14th International Workshop on Artificial Life and Evolutionary Computation, WIVACE 2019 ; Conference Date: 18 September 2019 Through 20 September 2019; Conference Code:242369},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85088752573&doi=10.1007%2f978-3-030-45016-8_10&partnerID=40&md5=c3f826c521c813005f58d344560648a2},
abstract = {Differential Evolution for Neural Networks (DENN) is an optimizer for neural network weights based on Differential Evolution. Although DENN has shown good performance with middle-size networks, the number of weights is an evident limitation of the approach. The aim of this work is to figure out if coevolutionary strategies implemented on top of DENN could be of help during the optimization phase. Moreover, we studied two of the classical problems connected to the application of evolutionary computation, i.e. the stagnation and the lack of population diversity, and the use of a crowding strategy to address them. The system has been tested on classical benchmark classification problems and experimental results are presented and discussed. © Springer Nature Switzerland AG 2020.},
author_keywords = {Coevolution; Differential Evolution; Neuroevolution},
keywords = {Artificial life; Calculations; Evolutionary algorithms; Optimization, Benchmark classification; Classical problems; Co-evolutionary; Differential Evolution; Network weights; Optimizers; Population diversity, Neural networks},
publisher = {Springer},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti202080,
author = {Baioletti, M. and Capotorti, A.},
title = {A L1 Minimization Optimal Corrective Explanation Procedure for Probabilistic Databases},
journal = {Communications in Computer and Information Science},
year = {2020},
volume = {1237 CCIS},
pages = {80-92},
doi = {10.1007/978-3-030-50146-4_7},
note = {Conference of 18th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2020 ; Conference Date: 15 June 2020 Through 19 June 2020; Conference Code:240699},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086276243&doi=10.1007%2f978-3-030-50146-4_7&partnerID=40&md5=8a786ce2e3843ebbbe08d7330d30c0d9},
abstract = {We propose to use a, recently introduced, efficient L1 distance minimization through mixed-integer linear programming for minimizing the number of valuations to be modified inside an incoherent probabilistic assessment. This is in line with one basic principle of optimal corrective explanation for decision makers. A shrewd use of constraints and of slack variables permit to steer the correction of incoherent assessments towards aimed directions, like e.g. the minimal number of changes. Such corrective explanations can be searched alone, as minimal changes, or jointly with the property of being also inside the L1 distance minimizers (in a bi-optimal point of view). The detection of such bi-optimal solutions can be performed efficiently by profiting from the geometric characterization of the whole set of L1 minimizers and from the properties of L1 topology. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Incoherence corrections; L1 constrained minimization; Mixed Integer Programming; Optimal corrective explanation; Probabilistic databases},
keywords = {Decision making; Geometry; Information management; Integer programming, Basic principles; Distance minimizations; Geometric characterization; Minimizing the number of; Mixed integer linear programming; Optimal solutions; Probabilistic assessments; Probabilistic database, Knowledge based systems},
publisher = {Springer},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti202018,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {An Algebraic Approach for the Search Space of Permutations with Repetition},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2020},
volume = {12102 LNCS},
pages = {18-34},
doi = {10.1007/978-3-030-43680-3_2},
note = {Conference of 20th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2020, held as part of Evostar 2020 ; Conference Date: 15 April 2020 Through 17 April 2020; Conference Code:239999},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85084982191&doi=10.1007%2f978-3-030-43680-3_2&partnerID=40&md5=8075322972f11a123c3f9664bd7b1369},
abstract = {We present an algebraic approach for dealing with combinatorial optimization problems based on permutations with repetition. The approach is an extension of an algebraic framework defined for combinatorial search spaces which can be represented by a group (in the algebraic sense). Since permutations with repetition does not have the group structure, in this work we derive some definitions and we devise discrete operators that allow to design algebraic evolutionary algorithms whose search behavior is in line with the algebraic framework. In particular, a discrete Differential Evolution algorithm which directly works on the space of permutations with repetition is defined and analyzed. As a case of study, an implementation of this algorithm is provided for the Job Shop Scheduling Problem. Experiments have been held on commonly adopted benchmark suites, and they show that the proposed approach obtains competitive results compared to the known optimal objective values. © 2020, Springer Nature Switzerland AG.},
author_keywords = {Algebraic approach; Discrete evolutionary algorithms; Permutations with Repetition},
keywords = {Algebra; Combinatorial optimization; Evolutionary algorithms; Job shop scheduling; Optimization, Algebraic approaches; Algebraic framework; Benchmark suites; Combinatorial optimization problems; Combinatorial search; Discrete differential evolution algorithm; Discrete operators; Job shop scheduling problems, Combinatorial mathematics},
publisher = {Springer},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2020,
author = {Baioletti, M. and Di Bari, G. and Milani, A. and Poggioni, V.},
title = {Differential evolution for neural networks optimization},
journal = {Mathematics},
year = {2020},
volume = {8},
number = {1},
doi = {10.3390/math8010069},
art_number = {69},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85079213868&doi=10.3390%2fmath8010069&partnerID=40&md5=53368e7ec301f8e0899e38125d788bdb},
abstract = {In this paper, a Neural Networks optimizer based on Self-adaptive Differential Evolution is presented. This optimizer applies mutation and crossover operators in a new way, taking into account the structure of the network according to a per layer strategy. Moreover, a new crossover called interm is proposed, and a new self-adaptive version of DE called MAB-ShaDE is suggested to reduce the number of parameters. The framework has been tested on some well-known classification problems and a comparative study on the various combinations of self-adaptive methods, mutation, and crossover operators available in literature is performed. Experimental results show that DENN reaches good performances in terms of accuracy, better than or at least comparable with those obtained by backpropagation. © 2020 by the authors. Licensee MDPI, Basel, Switzerland.},
author_keywords = {Differential evolution; Neural networks; Neuroevolution},
publisher = {MDPI AG},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti202037,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {Variable neighborhood algebraic Differential Evolution: An application to the Linear Ordering Problem with Cumulative Costs},
journal = {Information Sciences},
year = {2020},
volume = {507},
pages = {37-52},
doi = {10.1016/j.ins.2019.08.016},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070783784&doi=10.1016%2fj.ins.2019.08.016&partnerID=40&md5=c00ce6889da78c5eb19f1fd6a2034ad8},
abstract = {Algebraic variants of the Differential Evolution (DE) algorithm have been recently proposed to tackle permutation-based optimization problems by means of an algebraic framework, which allows to directly encode the solutions as permutations. The algebraic DE in the permutation space can be characterized by considering different neighborhood definitions such as swapping two adjacent items, swapping any two items, shifting an item to a given position. Here we propose the Variable Neighborhood Differential Evolution for Permutations (VNDEP), which adaptively searches the three neighborhoods together based on a method of dynamic reward. We provide an extensive and systematic analysis of the theoretical tools required in VNDEP, by studying the complexity of the proposed algorithmic components and by introducing the possibility to use a scale factor parameter larger than one. Experiments have been held on a widely used benchmark suite for the Linear Ordering Problem with Cumulative Costs, where VNDEP has been compared with four known permutation-based DE schemes and with respect to the state-of-the-art results for the considered instances. The experiments clearly show that VNDEP systematically outperforms the competitor algorithms and, most impressively, 32 new best known solutions, of the 50 most challenging instances, have been obtained. © 2019 Elsevier Inc.},
author_keywords = {Adaptive differential evolution; Algebraic differential evolution; Discrete differential evolution; Linear Ordering Problem with Cumulative Costs; Variable neighborhood search},
keywords = {Algebra; Evolutionary algorithms; Parallel processing systems; Set theory, Adaptive differential evolutions; Cumulative cost; Differential Evolution; Discrete differential evolutions; Variable neighborhood search, Optimization},
publisher = {Elsevier Inc.},
document_type = {Article},
source = {Scopus}
}
@article{Santucci2019,
author = {Santucci, V. and Milani, A. and Caraffini, F.},
title = {An optimisation-driven prediction method for automated diagnosis and prognosis},
journal = {Mathematics},
year = {2019},
volume = {7},
number = {11},
doi = {10.3390/math7111051},
art_number = {1051},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85075373719&doi=10.3390%2fmath7111051&partnerID=40&md5=ead299d48c5298ec6578a30f9f8269a3},
abstract = {This article presents a novel hybrid classification paradigm for medical diagnoses and prognoses prediction. The core mechanism of the proposed method relies on a centroid classification algorithm whose logic is exploited to formulate the classification task as a real-valued optimisation problem. A novel metaheuristic combining the algorithmic structure of Swarm Intelligence optimisers with the probabilistic search models of Estimation of Distribution Algorithms is designed to optimise such a problem, thus leading to high-accuracy predictions. This method is tested over 11 medical datasets and compared against 14 cherry-picked classification algorithms. Results show that the proposed approach is competitive and superior to the state-of-the-art on several occasions. © 2019 by the authors.},
author_keywords = {Automated diagnosis; Classification; Estimation of distribution algorithms; Hybrid algorithms; Particle swarm optimization},
publisher = {MDPI AG},
document_type = {Article},
source = {Scopus}
}
@conference{Franzoni201991,
author = {Franzoni, V. and Milani, A. and Biondi, G. and Micheli, F.},
title = {A preliminary work on dog emotion recognition},
journal = {Proceedings - 2019 IEEE/WIC/ACM International Conference on Web Intelligence Workshops, WI 2019 Companion},
year = {2019},
pages = {91-96},
doi = {10.1145/3358695.3361750},
note = {Conference of 19th IEEE/WIC/ACM International Conference on Web Intelligence Workshop, WI 2019 ; Conference Date: 14 October 2019 Through 17 October 2019; Conference Code:152685},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074373338&doi=10.1145%2f3358695.3361750&partnerID=40&md5=28643a3c506d284761d30c4e16a889af},
abstract = {Humans react to animal emotions, and animals react to human emotions because we share similar emotional and neurological mirroring systems. Mirror neurons fire both when an animal performs an action and when the animal observes the same action performed by another individual. This neurological system has been linked to social behaviors and abilities, from empathy to learning by imitation, both in intra-species and in inter-species communications. The aim of this paper is to study if a machine learning system can recognize animal emotions, starting from dogs' basic emotions of joy and anger, and to investigate the opportunity of future applications concerning systems of prosthetic knowledge to help people without the proper experience or capability to understand animals aggressivity or friendliness, or for supportive systems in Artificial Intelligence. © 2019 Copyright held by the owner/author(s).},
author_keywords = {Affective computing; Artificial intelligence; Emotion recognition; Neural networks; Transfer learning},
keywords = {Animals; Artificial intelligence; Behavioral research; Neural networks; Neurology; Speech recognition, Affective Computing; Basic emotions; Emotion recognition; Future applications; Learning by imitation; Mirror neurons; Social behavior; Transfer learning, Learning systems},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Vallverdù201986,
author = {Vallverdù, J. and Franzoni, V. and Milani, A.},
title = {Errors, biases and overconfidence in artificial emotional modeling},
journal = {Proceedings - 2019 IEEE/WIC/ACM International Conference on Web Intelligence Workshops, WI 2019 Companion},
year = {2019},
pages = {86-90},
doi = {10.1145/3358695.3361749},
note = {Conference of 19th IEEE/WIC/ACM International Conference on Web Intelligence Workshop, WI 2019 ; Conference Date: 14 October 2019 Through 17 October 2019; Conference Code:152685},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074356529&doi=10.1145%2f3358695.3361749&partnerID=40&md5=42717088f0c05e9b32f898c5ca4513d4},
abstract = {With the diffusion and successful new implementation of several machine learning techniques, together with the substantial cost decrease of sensors, also included in mobile devices, the field of emotional analysis and modeling has boosted. Apps, web apps, brain-scanning devices, and Artificial Intelligence assistants often include emotion recognition features or emotional behaviors, but new researches contain, maintain, or create several design errors, which analysis is the main aim of this paper. © 2019 Copyright held by the owner/author(s).},
author_keywords = {Affective computing; Emotion; Errors; Gendered; HRI; Overconfidence},
keywords = {Artificial intelligence; Errors, Affective Computing; Emotion; Emotion recognition; Emotional analysis; Emotional behavior; Gendered; Machine learning techniques; Overconfidence, Learning systems},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti20191535,
author = {Baioletti, M. and Santucci, V. and Milani, A. and Tomassini, M.},
title = {Search moves in the local optima networks of permutation spaces: The QAP case},
journal = {GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion},
year = {2019},
pages = {1535-1542},
doi = {10.1145/3319619.3326849},
note = {Conference of 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 ; Conference Date: 13 July 2019 Through 17 July 2019; Conference Code:149527},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070632646&doi=10.1145%2f3319619.3326849&partnerID=40&md5=859237ecda89b4f1412ceb8be88a7485},
abstract = {In this work we analyze, from a qualitative point-of-view, the structure of the connections among the local optima in the fitness landscapes of the Quadratic Assignment Problem (QAP). In particular, we are interested in determining which search moves, intended as pairwise exchanges of permutation items, are beneficial for moving from one optimum to another. Novel algebraic methods are introduced for determining, and measuring the effectiveness, of the exchange moves connecting two given optima. The analysis considers real-like QAP instances whose local optima networks are clustered in communities. The results of the conducted experimentation shows the presence of few preferred search moves that look more effective for moving across intra-community optima, while the same is not so apparent when the optima are taken from different communities. © 2019 Association for Computing Machinery.},
author_keywords = {Algebraic Evolutionary Computation; Fitness Landscape Analysis; Quadratic Assignment Problem},
keywords = {Calculations; Combinatorial optimization, Algebraic method; Fitness landscape; Fitness landscape analysis; Local optima; Pair-wise exchanges; Quadratic assignment problems, Algebra},
sponsors = {ACM SIGEVO},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti20191527,
author = {Baioletti, M. and Santucci, V. and Milani, A. and Bartoccini, U.},
title = {An experimental comparison of algebraic differential evolution using different generating sets},
journal = {GECCO 2019 Companion - Proceedings of the 2019 Genetic and Evolutionary Computation Conference Companion},
year = {2019},
pages = {1527-1534},
doi = {10.1145/3319619.3326854},
note = {Conference of 2019 Genetic and Evolutionary Computation Conference, GECCO 2019 ; Conference Date: 13 July 2019 Through 17 July 2019; Conference Code:149527},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85070602968&doi=10.1145%2f3319619.3326854&partnerID=40&md5=28e2078d6594f7c54199f7f42f34e27b},
abstract = {In this paper we provide a comparative empirical analysis of four different generating sets for the algebraic Differential Evolution for Permutations (DEP) applied to the Traveling Salesman Problem (TSP). In particular, DEP has been extended in order to use the reversal moves as generating set. Two different randomized decomposers are proposed for the reversal generators. The experiments have been conducted on a selected set of commonly adopted TSP instances, and the results show the newly proposed generating set leads to better performances with respect to other three generating sets based on alternative search moves. © 2019 Association for Computing Machinery.},
author_keywords = {Algebraic Differential Evolution; Sorting by Reversals; Traveling Salesman Problem},
keywords = {Algebra; Evolutionary algorithms; Optimization, Decomposers; Differential Evolution; Empirical analysis; Experimental comparison; Generating set; Sorting by reversals, Traveling salesman problem},
sponsors = {ACM SIGEVO},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2019,
author = {Milani, A. and Franzoni, V. and Biondi, G. and Li, Y.},
title = {Integrating Binary Similarity Measures in the Link Prediction Task},
journal = {Proceedings - 2018 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018},
year = {2019},
doi = {10.1109/CISP-BMEI.2018.8633089},
art_number = {8633089},
note = {Conference of 11th International Congress on Image and Signal Processing, BioMedical Engineering and Informatics, CISP-BMEI 2018 ; Conference Date: 13 October 2018 Through 15 October 2018; Conference Code:144766},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062855772&doi=10.1109%2fCISP-BMEI.2018.8633089&partnerID=40&md5=39e431b4f67b75366688b067f1011c76},
abstract = {In this work we investigate the applicability of binary similarity and distance measures in the context of Link Prediction. Neighbourhood-based similarity measures to assess the similarity of nodes in a network have been long available. They boast the main advantage of low calculation complexity, because only a local view of the network is required. Neighbourhood-based measures are used in a variety of Link Prediction applications, including bioinformatics, bibliographic networks and recommender systems. It is possible to use binary measures in the same context, retaining the same prerogatives and possibly increasing the link prediction performances in domain-specific tasks. Preliminary studies have also been conducted on widely-accepted data sets. © 2018 IEEE.},
keywords = {Biomedical engineering; Image processing, Binary similarity measures; Distance measure; Domain specific; Link prediction; Neighbourhood; Similarity measure, Forecasting},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2019112,
author = {Baioletti, M. and Capotorti, A.},
title = {A L1 based probabilistic merging algorithm and its application to statistical matching},
journal = {Applied Intelligence},
year = {2019},
volume = {49},
number = {1},
pages = {112-124},
doi = {10.1007/s10489-018-1233-z},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85050357109&doi=10.1007%2fs10489-018-1233-z&partnerID=40&md5=5ea3ebd4748e1339c815a561d10123de},
abstract = {We propose to use a recently introduced merging procedure for jointly inconsistent probabilistic assessments to the statistical matching problem. The merging procedure is based on an efficient L1 distance minimization through mixed-integer linear programming. Significance of the method can be appreciated whenever among quantities (events) there are logical (structural) constraints and there are different sources of information. Statistical matching problem has these features and is characterized by a set of random (discrete) variables that cannot be jointly observed. Separate observations share anyhow some common variable, and this, together with structural constraints, make sometimes inconsistent the estimates of probability occurrences. Even though estimates on statistical matching are mainly conditional probabilities, inconsistencies appear only on events with the same conditioning, hence the correction procedure can be easily reduced to unconditional cases and the aforementioned procedure applied. © 2018, Springer Science+Business Media, LLC, part of Springer Nature.},
author_keywords = {L1 constrained minimization; Mixed integer programming; Probabilistic merging; Statistical matching},
keywords = {Constrained optimization; Merging; Statistics, Conditional probabilities; Constrained minimization; Mixed integer linear programming; Mixed integer programming; Probabilistic assessments; Sources of informations; Statistical matching; Structural constraints, Integer programming},
publisher = {Springer New York LLC},
document_type = {Article},
source = {Scopus}
}
@article{Yeoh20191,
author = {Yeoh, J.M. and Caraffini, F. and Homapour, E. and Santucci, V. and Milani, A.},
title = {A clustering system for dynamic data streams based on metaheuristic optimisation},
journal = {Mathematics},
year = {2019},
volume = {7},
number = {12},
pages = {1-24},
doi = {10.3390/math7121229},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85077546535&doi=10.3390%2fmath7121229&partnerID=40&md5=686d41c014609ec2204ab69edc1e5fdd},
abstract = {This article presents the Optimised Stream clustering algorithm (OpStream), a novel approach to cluster dynamic data streams. The proposed system displays desirable features, such as a low number of parameters and good scalability capabilities to both high-dimensional data and numbers of clusters in the dataset, and it is based on a hybrid structure using deterministic clustering methods and stochastic optimisation approaches to optimally centre the clusters. Similar to other state-of-the-art methods available in the literature, it uses "microclusters" and other established techniques, such as density based clustering. Unlike other methods, it makes use of metaheuristic optimisation to maximise performances during the initialisation phase, which precedes the classic online phase. Experimental results show that OpStream outperforms the state-of-the-art methods in several cases, and it is always competitive against other comparison algorithms regardless of the chosen optimisation method. Three variants of OpStream, each coming with a different optimisation algorithm, are presented in this study. A thorough sensitive analysis is performed by using the best variant to point out OpStream's robustness to noise and resiliency to parameter changes. © 2019 by the authors.},
author_keywords = {Concept drift; Concept evolution; Density based clustering; Dynamic streamclustering; K-means centroid; Metaheuristics; Online clustering; Optimisation; Population based algorithms},
publisher = {MDPI AG},
document_type = {Article},
source = {Scopus}
}
@conference{Franzoni201932,
author = {Franzoni, V. and Biondi, G. and Milani, A.},
title = {Crowd emotional sounds: Spectrogram-based analysis using convolutional neural networks},
journal = {CEUR Workshop Proceedings},
year = {2019},
volume = {2474},
pages = {32-36},
note = {Conference of 2019 Socio-Affective Technologies: An Interdisciplinary Approach, SAT 2019 ; Conference Date: 7 October 2019; Conference Code:152702},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85074067588&partnerID=40&md5=d973ef893ff1e0b6c8ad5e619a758843},
abstract = {In this work, we introduce a methodology for the recognition of crowd emotions from crowd speech and sound in mass events. Different emotional categories can be encoded via frequency-amplitude features of emotional crowd speech. The proposed technique uses visual transfer learning applied to the input sound spectrograms. Spectrogram images are generated starting from snippets of fixed length taken from the original sound clip. The plots are then filtered and normalized concerning frequency and magnitude and then fed to a pre-trained Convolutional Neural Network (CNN) for images (AlexNet) integrated with domain-specific categorical layers. The integrated CNN is re-trained with the labeled spectrograms of crowd emotion sounds in order to adapt and fine-tune the recognition of the crowd emotional categories. Preliminary experiments have been held on a dataset collecting publicly-available sound clips of different mass events for each class, including Joy, Anger and Neutral. While transfer learning has been applied in existing literature to music and speech processing, to the best of our knowledge, this is the first application to crowd-sound emotion recognition. Copyright © 2019 for this paper by its authors.},
author_keywords = {CNN; Crowd computing; Crowd emotions; Emotion recognition; Image recognition; Transfer learning},
keywords = {Convolution; Image recognition; Multilayer neural networks; Spectrographs; Speech processing, Convolutional neural network; Crowd computing; Crowd emotions; Different mass; Domain specific; Emotion recognition; Sound emotion recognition; Transfer learning, Speech recognition},
publisher = {CEUR-WS},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2019336,
author = {Franzoni, V. and Tasso, S. and Pallottelli, S. and Perri, D.},
title = {Sharing Linkable Learning Objects with the Use of Metadata and a Taxonomy Assistant for Categorization},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11620 LNCS},
pages = {336-348},
doi = {10.1007/978-3-030-24296-1_28},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069220124&doi=10.1007%2f978-3-030-24296-1_28&partnerID=40&md5=3fe374242f289622887f4f0fe920d22e},
abstract = {In this work, a re-design of the Moodledata module functionalities is presented to share learning objects between e-learning content platforms, e.g., Moodle and G-Lorep, in a linkable object format. The e-learning courses content of the Drupal-based Content Management System G-Lorep for academic learning is exchanged designing an object incorporating metadata to support the reuse and the classification in its context. In such an Artificial Intelligence environment, the exchange of Linkable Learning Objects can be used for dialogue between Learning Systems to obtain information, especially with the use of semantic or structural similarity measures to enhance the existent Taxonomy Assistant for advanced automated classification. © 2019, Springer Nature Switzerland AG.},
author_keywords = {CMS; E-learning; G-Lorep; Learning management system; Learning object; Linked data; LMS; Moodle},
keywords = {Curium; Curricula; E-learning; Information management; Linked data; Metadata; Semantics; Taxonomies, Automated classification; Content management system; E-learning contents; G-Lorep; Learning management system; Learning objects; Moodle; Structural similarity, Learning systems},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Mengoni2019323,
author = {Mengoni, P. and Milani, A. and Li, Y.},
title = {Impact of Time Granularity on Histories Binary Correlation Analysis},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11620 LNCS},
pages = {323-335},
doi = {10.1007/978-3-030-24296-1_27},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069211286&doi=10.1007%2f978-3-030-24296-1_27&partnerID=40&md5=a7e9d65c4250992297d0dbe86ab8b3dc},
abstract = {Activities taken by students within a Virtual Learning Environment (VLE) can be represented by using binary student histories. Virtual Learning Environments allow educators to track most of the students’ individual activities that can be used to elicit the students social communities. In this work, we analyse the impact of granularity in the social community elicitation. Granularity can be seen as the resolution of the student history vectors where each time slot is directly dependent from this value. Indeed, the higher is the resolution of the students histories the more precise is the representation of their actions within the VLE. When comparing the histories using various similarity measures to elicit the students’ groups, we find the optimal granularity and demonstrate that there is a resolution limit where the similarity measures will not help to distinguish the social communities. © 2019, Springer Nature Switzerland AG.},
author_keywords = {Cluster analysis; Community elicitation; Data analysis; Learning analytics},
keywords = {Cluster analysis; Computer aided instruction; Data reduction; E-learning, Binary correlations; Community elicitation; Learning analytics; Resolution limits; Similarity measure; Social communities; Time granularities; Virtual learning environments, Students},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Science and Business Media Deutschland GmbH},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Biondi2019649,
author = {Biondi, G. and Franzoni, V. and Gervasi, O. and Perri, D.},
title = {An Approach for Improving Automatic Mouth Emotion Recognition},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11619 LNCS},
pages = {649-664},
doi = {10.1007/978-3-030-24289-3_48},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069176942&doi=10.1007%2f978-3-030-24289-3_48&partnerID=40&md5=acd31947421b8826f3ab1bc710f1c7d2},
abstract = {The study proposes and tests a technique for automated emotion recognition through mouth detection via Convolutional Neural Networks (CNN), meant to be applied for supporting people with health disorders with communication skills issues (e.g. muscle wasting, stroke, autism, or, more simply, pain) in order to recognize emotions and generate real-time feedback, or data feeding supporting systems. The software system starts the computation identifying if a face is present on the acquired image, then it looks for the mouth location and extracts the corresponding features. Both tasks are carried out using Haar Feature-based Classifiers, which guarantee fast execution and promising performance. If our previous works focused on visual micro-expressions for personalized training on a single user, this strategy aims to train the system also on generalized faces data sets. © 2019, Springer Nature Switzerland AG.},
keywords = {Neural networks; Real time systems, Communication skills; Convolutional neural network; Emotion recognition; Health disorders; Micro-expressions; Real-time feedback; Software systems; Supporting systems, Speech recognition},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2019391,
author = {Franzoni, V. and Milani, A.},
title = {Emotion Recognition for Self-aid in Addiction Treatment, Psychotherapy, and Nonviolent Communication},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11620 LNCS},
pages = {391-404},
doi = {10.1007/978-3-030-24296-1_32},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069166203&doi=10.1007%2f978-3-030-24296-1_32&partnerID=40&md5=9fd3cca43de6e1c5747776bab3c03cf0},
abstract = {This position paper aims to highlight possible future directions of applications for Affective Computing (AC) and Emotion Recognition (ER) for self-aid applications, as they emerge from the experience of the ACER-EMORE Workshops Series. ER in Artificial Intelligence offers a growing number of problem-solving multidisciplinary opportunities. Most current AC and ER applications are focused on a somewhat controversial enterprise-centered approach, i.e., recognizing user emotions to enable a third-party to achieve its own goals, in areas such as e-commerce, cybersecurity, behavior profiling, user experience. In this work we propose to explore a human-centered research direction, aiming at using AC/ER to enhance user consciousness of emotional states, ultimately supporting the development of self-aid applications. The use of facial ER and text ER to help forms of assistive technologies in the fields of Psychotherapy and Communication is an example of such a human-centered approach. A general framework for ER in Self-aid is depicted, and some relevant application domains are suggested and discussed: dependencies treatment (DT) (e.g., workaholism, sexaholism); non-violent communication (NVC) for people in leading roles using e-mail or chat communication; empathy learning for parents and teachers in the circle-of-security (COS) caring environment. Far from being complete and comprehensive, the purpose of this work is to trigger discussions and ideas for feasible studies and applications of ER in self-aid, which we hope to see published in the future editions of our workshops, believing that it may be one of the drops needed in the ocean of a better world. © 2019, Springer Nature Switzerland AG.},
author_keywords = {Assistive technologies; Circle of security; COS; Non-violent communication; NVC; Sexaholics; Workaholics},
keywords = {Cobalt; Problem solving; Speech recognition, Affective Computing; Assistive technology; Circle of security; Emotion recognition; Possible futures; Sexaholics; User experience; Workaholics, Behavioral research},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2019830,
author = {Milani, A. and Spina, S. and Santucci, V. and Piersanti, L. and Simonetti, M. and Biondi, G.},
title = {Text Classification for Italian Proficiency Evaluation},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11619 LNCS},
pages = {830-841},
doi = {10.1007/978-3-030-24289-3_61},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85069149119&doi=10.1007%2f978-3-030-24289-3_61&partnerID=40&md5=736910d186eaf863003efdc15dfc564b},
abstract = {NLP technologies and components have an increasing diffusion in mass analysis of text based dialogues, such as classifiers for sentiment polarity, trends clustering of online messages and hate speech detection. In this work we present the design and the implementation an automatic classification tool for the evaluation of the complexity of Italian texts as understood by a speaker of Italian as a second language. The classification is done within the Common European Framework of Reference for Languages (CEFR) which aims at classifying speakers language proficiency. Results of preliminary experiments on a data set of real texts, annotated by experts and used in actual CEFR exam sessions, show a strong ability of the proposed system to label texts with the correct language proficiency class and a great potential for its integration in learning tools, such systems supporting examiners in tests design and automatic evaluation of writing abilities. © 2019, Springer Nature Switzerland AG.},
author_keywords = {Language proficiency classifier; Learning systems; PoS; Text classifier},
keywords = {Classification (of information); Learning systems; Polonium; Statistical tests, Automatic classification; Automatic evaluation; Language proficiency; Second language; Speech detection; Text classification; Text classifiers; Writing abilities, Text processing},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2019513,
author = {Franzoni, V. and Li, Y. and Milani, A.},
title = {Set Semantic Similarity for Image Prosthetic Knowledge Exchange},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11624 LNCS},
pages = {513-525},
doi = {10.1007/978-3-030-24311-1_37},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068607022&doi=10.1007%2f978-3-030-24311-1_37&partnerID=40&md5=7c9d1f6e12b21244ebacaa95deaebf2e},
abstract = {Concept information can be expressed by text, images or general objects which semantic meaning is clear to a human in a specific cultural context. For a computer, when available, text with its semantics (e.g., metadata, comments, captions) can convey more precise meaning than images or general objects with low-level features (e.g., color distribution, shapes, sound peaks) to extract the concept underlying the object. Among semantic measures, web-based proximity measures e.g., confidence, PMING, NGD, Jaccard, Dice, are particularly useful for concept evaluation, exploiting statistical data provided by search engines on terms and expressions provided in texts associated with the object. Where Artificial Intelligence can be a support for impaired individuals, e.g., having disabilities related to vision and hearing, understanding the concept underlying an object can be critical for an intelligent artificial assistant. In this work we propose to use the set semantic distance, already used in literature for semantic similarity measurement of web objects, as a tool for artificial assistants to support knowledge extraction; in other words, as prosthetic knowledge. © 2019, Springer Nature Switzerland AG.},
author_keywords = {Artificial Intelligence; Assistants; Group distance; Information retrieval; Semantic proximity},
keywords = {Artificial intelligence; Audition; Information retrieval; Knowledge management; Prosthetics; Semantic Web; Semantics, Assistants; Color distribution; Concept evaluation; Group distance; Knowledge exchange; Low-level features; Proximity measure; Semantic similarity measurement, Search engines},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2019526,
author = {Milani, A. and Niyogi, R. and Biondi, G.},
title = {Neural Network Based Approach for Learning Planning Action Models},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11624 LNCS},
pages = {526-537},
doi = {10.1007/978-3-030-24311-1_38},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068598314&doi=10.1007%2f978-3-030-24311-1_38&partnerID=40&md5=419ca67bf63b3ed3abc9d8a5388960e5},
abstract = {Artificial Intelligence (AI) planning technology represents one of the most efficient solutions to guide goal driven agents in domain problems which are mostly characterized by problem solving features. The current proliferation of physical and virtual autonomous agents have therefore triggered a growing interest in the automatic acquisition of action models, which can take advantage of the observation capabilities of agents, which sense world states through their sensors. In this work we present a Neural Network (NN) based approach for learning AI planning action models by observation in noisy environments. The system learns by observing a set of execution patterns of the same action in different contexts. The perceptions of both pre/post action execution states are used to train the NN learning component and are assumed to be affected by noise, which could be due to inaccurate reading or malfunctioning of the sensors. Preliminary experiments shows that the proposed NN learning module seems to be more resilient to unforeseen situations with respect to traditional propositional-based approaches to action model learning. © 2019, Springer Nature Switzerland AG.},
author_keywords = {Neural Networks; Planning},
keywords = {Autonomous agents; Neural networks; Planning; Problem solving, Action execution; Automatic acquisition; Domain problems; Learning modules; Network-based approach; Neural network (nn); Noisy environment; Virtual autonomous agents, Learning systems},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Tasso2019359,
author = {Tasso, S. and Pallottelli, S. and Gervasi, O. and Sabbatini, F. and Franzoni, V. and Laganà, A.},
title = {Cloud and Local Servers for a Federation of Molecular Science Learning Object Repositories},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11624 LNCS},
pages = {359-373},
doi = {10.1007/978-3-030-24311-1_26},
note = {Conference of 19th International Conference on Computational Science and Its Applications, ICCSA 2019 ; Conference Date: 1 July 2019 Through 4 July 2019; Conference Code:227949},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85068591975&doi=10.1007%2f978-3-030-24311-1_26&partnerID=40&md5=7310d9a12e1574fc15f55b4cf6fcb7a5},
abstract = {The G-Lorep project of the European Chemistry Thematic Network (ECTN), based on a federation of distributed repositories of Molecular Science Learning Objects, leverages at present a “hybrid” centralized/distributed architecture in which the central node hosts a shared database. The shared database deals only with the task of managing metadata to the end of synchronizing the information made available to the federation members at regular time intervals. In order to avoid missed synchronization (in the case of the failure of the central node) a scheme distributing the nodes, adopting a PaaS (Platform as a Service) strategy and ensuring network security, is implemented and related performances are evaluated. The efficiency of the developed new architecture of the federation is measured for a set of Molecular Science Learning Objects developed within some European distributed computing initiatives and adopted for the Theoretical Chemistry and Computational Modeling European Master and Doctoral joint courses. The evolution of the proposed Learning Objects is discussed also in view of the development of the Molecular Simulator Enabled Cloud Services (MOSEX) pilot project. © 2019, Springer Nature Switzerland AG.},
author_keywords = {Chemical reactions; Cloud; Distributed systems; Learning objects; Molecular Science; PaaS; Repositories; Security; Synchronization},
keywords = {Chemical reactions; Clouds; Computational chemistry; Learning systems; Network architecture; Network security; Synchronization, Distributed systems; Learning objects; Molecular science; PaaS; Repositories; Security, Platform as a Service (PaaS)},
sponsors = {et al.; Monash University, Australia; Springer Nature Switzerland AG, Germany; St. Petersburg University, Russia; University of Basilicata, Italy; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Santucci2019133,
author = {Santucci, V. and Baioletti, M. and Milani, A.},
title = {Tackling Permutation-based Optimization Problems with an Algebraic Particle Swarm Optimization Algorithm},
journal = {Fundamenta Informaticae},
year = {2019},
volume = {167},
number = {1-2},
pages = {133-158},
doi = {10.3233/FI-2019-1812},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85067015679&doi=10.3233%2fFI-2019-1812&partnerID=40&md5=0170a7f3ac38169ef1602821007dc4a0},
abstract = {Particle Swarm Optimization (PSO), though originally introduced for continuous search spaces, has been increasingly applied to combinatorial optimization problems. In this paper, we focus on the PSO applications to permutation-based problems. As far as we know, the most popular and general PSO schemes for permutation solutions are those based on random key techniques. After highlighting the main criticalities of the random key approach, we introduce a discrete PSO variant for permutation-based optimization problems. By simulating search moves through a vector space, the proposed algorithm, Algebraic PSO (APSO), allows the original PSO design to be applied to the permutation search space. APSO directly represents both particlepositions and velocities as permutations. The APSO search scheme is based on a general algebraic framework for combinatorial optimization based on strong mathematical foundations. However, in order to make this new scheme viable, some challenges have to be overcome: the choice of the order of the velocity terms, and the rationale behind the PSO inertial move. Design solutions have been proposed for both the issues. Furthermore, an alternative geometric interpretation of classical PSO dynamics allows to introduce a major APSO variant based on a novel concept of convex combination between permutation objects. In total, four APSO schemes have been introduced. Experiments have been held to compare the performances of the APSO schemes with respect to the random key based PSO schemes in literature. Widely adopted benchmark instances of four popular permutation problems have been considered. The experimental results clearly show that, with high statistical evidence, APSO outperforms its competitors and it reaches results comparable with state-of-the-art on most of the instances considered. © 2019 IOS Press. All rights reserved.},
author_keywords = {Algebraic Particle Swarm Optimization; Permutation Problems; Permutation Search Space},
keywords = {Benchmarking; Combinatorial optimization; Vector spaces, Combinatorial optimization problems; Geometric interpretation; Mathematical foundations; Optimization problems; Particle swarm optimization algorithm; Permutation problems; Search spaces; Statistical evidence, Particle swarm optimization (PSO)},
publisher = {IOS Press},
document_type = {Article},
source = {Scopus}
}
@article{Santucci201917,
author = {Santucci, V. and Baioletti, M. and Di Bari, G. and Milani, A.},
title = {A binary algebraic differential evolution for the multidimensional two-way number partitioning problem},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2019},
volume = {11452 LNCS},
pages = {17-32},
doi = {10.1007/978-3-030-16711-0_2},
note = {Conference of 19th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2019, held as part of EvoStar 2019 ; Conference Date: 24 April 2019 Through 26 April 2019; Conference Code:225209},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85064911861&doi=10.1007%2f978-3-030-16711-0_2&partnerID=40&md5=5061b51308e781708134190c369962db},
abstract = {This paper introduces MADEB, a Memetic Algebraic Differential Evolution algorithm for the Binary search space. MADEB has been applied to the Multidimensional Two-Way Number Partitioning Problem (MDTWNPP) and its main components are the binary differential mutation operator and a variable neighborhood descent procedure. The binary differential mutation is a concrete application of the abstract algebraic framework for the binary search space. The variable neighborhood descent is a local search procedure specifically designed for MDTWNPP. Experiments have been held on a widely accepted benchmark suite and MADEB is experimentally compared with respect to the current state-of-the-art algorithms for MDTWNPP. The experimental results clearly show that MADEB is the new state-of-the-art algorithm in the problem here investigated. © Springer Nature Switzerland AG 2019.},
author_keywords = {Binary algebraic differential evolution; Multidimensional Two-Way Number Partitioning Problem; Variable neighborhood descent},
keywords = {Algebra; Combinatorial optimization; Optimization, Algebraic framework; Concrete applications; Differential Evolution; Differential evolution algorithms; Differential mutations; Number partitioning problems; State-of-the-art algorithms; Variable neighborhood descents, Evolutionary algorithms},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Gervasi201917,
author = {Gervasi, O. and Franzoni, V. and Riganelli, M. and Tasso, S.},
title = {Automating facial emotion recognition},
journal = {Web Intelligence},
year = {2019},
volume = {17},
number = {1},
pages = {17-27},
doi = {10.3233/WEB-190397},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062171971&doi=10.3233%2fWEB-190397&partnerID=40&md5=79b435ff7cd4b2159db56788b0306880},
abstract = {The work described in this paper attempts to contribute to one of the most stimulating and promising sectors in the field of emotion recognition, which is health care. Multidisciplinary studies in artificial intelligence, augmented reality, and psychology stressed out the importance of emotions in communication and awareness. The intent is the recognition of human emotions, processing images streamed in real-time from a mobile device. The proposed techniques involve the use of open source libraries of visual recognition and machine learning approaches based on convolutional neural networks (CNN). © 2019-IOS Press and the authors. All rights reserved.},
author_keywords = {convolutional neural networks; emotion recognition; face detection; Image recognition; machine learning},
keywords = {Augmented reality; Convolution; Image recognition; Learning systems; Machine learning; Neural networks; Speech recognition, Convolutional neural network; Emotion recognition; Facial emotions; Human emotion; Machine learning approaches; Open-source libraries; Real time; Visual recognition, Face recognition},
publisher = {IOS Press},
document_type = {Article},
source = {Scopus}
}
@article{Franzoni20191,
author = {Franzoni, V. and Milani, A. and Nardi, D. and Vallverdú, J.},
title = {Emotional machines: The next revolution},
journal = {Web Intelligence},
year = {2019},
volume = {17},
number = {1},
pages = {1-7},
doi = {10.3233/WEB-190395},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85062169814&doi=10.3233%2fWEB-190395&partnerID=40&md5=966c53366fc3cb8b35d0fd8d34fea696},
publisher = {IOS Press},
document_type = {Review},
source = {Scopus}
}
@conference{Franzoni2018332,
author = {Franzoni, V. and Mengoni, P. and Milani, A.},
title = {Dimensional morphing interface for dynamic learning evaluation},
journal = {Information Visualisation - Biomedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2018},
year = {2018},
pages = {332-337},
doi = {10.1109/iV.2018.00063},
art_number = {8564181},
note = {Conference of 22nd International Conference Information Visualisation - Biomedical Visualization, Visualisation on Built and Rural Environments and Geometric Modelling and Imaging, IV 2018 ; Conference Date: 10 July 2018 Through 13 July 2018; Conference Code:143366},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85060182407&doi=10.1109%2fiV.2018.00063&partnerID=40&md5=b99bac248fd44a30023335fcb80c65bd},
abstract = {In this paper an innovative dynamic dimensional morphing metaphor is introduced to monitor students' engagement and cohort dynamic. Teachers using eLearning monitoring tools find them usually lacking usability and inadequate to give productive feedback about their learning designs. Learning analytics tools mostly focus on after course analysis with the assumption that user competence in data analysis is high. The tool we propose is based on visual interface morphing: reshaping of the interface elements, such as learning objects' links and icons, is put in place to reflect some key performance indicators of learners' activities. Quantitative and temporal analytics data, aggregated using various functions, is used to present animated enhanced information to teachers. Experiments for the assessment of the effectiveness of the proposed tool has been conducted on data from higher education courses. Through logs' analysis and teachers' questionnaires the usability and validity of the proposed metaphor has been assessed. The proposed tool outperforms traditional monitoring techniques. © 2018 IEEE.},
author_keywords = {eLearning; Learner monitoring; Learning design evaluation; Usability; Visual interfaces},
keywords = {Benchmarking; E-learning; Surveys; Teaching; Visualization, Interface elements; Key performance indicators; Learning analytics; Learning designs; Monitoring techniques; Students' engagements; Usability; Visual Interface, Learning systems},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Mudgal2018438,
author = {Mudgal, R.K. and Niyogi, R. and Milani, A. and Franzoni, V.},
title = {Analysis of tweets to find the basis of popularity based on events semantic similarity},
journal = {International Journal of Web Information Systems},
year = {2018},
volume = {14},
number = {4},
pages = {438-452},
doi = {10.1108/IJWIS-11-2017-0080},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057446824&doi=10.1108%2fIJWIS-11-2017-0080&partnerID=40&md5=9ec2ea316f2d32b724f705ca1fdeed6d},
abstract = {Purpose: The purpose of this paper is to propose and experiment a framework for analysing the tweets to find the basis of popularity of a person and extract the reasons supporting the popularity. Although the problem of analysing tweets to detect popular events and trends has recently attracted extensive research efforts, not much emphasis has been given to find out the reasons behind the popularity of a person based on tweets. Design/methodology/approach: In this paper, the authors introduce a framework to find out the reasons behind the popularity of a person based on the analysis of events and the evaluation of a Web-based semantic set similarity measure applied to tweets. The methodology uses the semantic similarity measure to group similar tweets in events. Although the tweets cannot contain identical hashtags, they can refer to a unique topic with equivalent or related terminology. A special data structure maintains event information, related keywords and statistics to extract the reasons supporting popularity. Findings: An implementation of the algorithms has been experimented on a data set of 218,490 tweets from five different countries for popularity detection and reasons extraction. The experimental results are quite encouraging and consistent in determining the reasons behind popularity. The use of Web-based semantic similarity measure is based on statistics extracted from search engines, it allows to dynamically adapt the similarity values to the variation on the correlation of words depending on current social trends. Originality/value: To the best of the authors’ knowledge, the proposed method for finding the reason of popularity in short messages is original. The semantic set similarity presented in the paper is an original asymmetric variant of a similarity scheme developed in the context of semantic image recognition. © 2018, Emerald Publishing Limited.},
author_keywords = {Event detection; Semantic analysis; Semantic similarity; Set similarity; Twitter},
keywords = {Data mining; Image recognition; Search engines; Semantics; Websites, Event detection; Semantic analysis; Semantic similarity; Set similarity; Twitter, Semantic Web},
publisher = {Emerald Group Holdings Ltd.},
document_type = {Article},
source = {Scopus}
}
@conference{Biondi20181483,
author = {Biondi, G. and Milani, A. and Baia, A.E.},
title = {Differential evolution of correlation indexes for link prediction},
journal = {Proceedings - 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018},
year = {2018},
pages = {1483-1486},
doi = {10.1109/CSCI46756.2018.00296},
art_number = {8947714},
note = {Conference of 2018 International Conference on Computational Science and Computational Intelligence, CSCI 2018 ; Conference Date: 13 December 2018 Through 15 December 2018; Conference Code:156537},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85078515241&doi=10.1109%2fCSCI46756.2018.00296&partnerID=40&md5=940df9c55fdc639c25f391fda63182aa},
abstract = {Determining the appropriate binary correlation indexes is a central issue for neighbourhood-based Link Prediction techniques. In those approaches correlation-based similarity measures, evaluated on the neighbourhood of a given pair of nodes in a training network, are used to assess the likelihood of those nodes developing new links in the future. It has been observed that, although some similarity measures generally perform better than others, no single binary correlation is optimal for all domains. In this work we introduce a technique which evolves a population of correlation indexes, using a Differential Evolution (DE) algorithm, in order to determine the binary correlation index having the best prediction performance with respect to specific network domains. DE evolves the parameters of meta-indexes, structures which describe and extend classes of known binary similarity indexes. Preliminary experiments show that the proposed correlation indexes evolution method has performances equivalent and in some cases improving the best correlation indexes known for each tested domain, while it provides the remarkable advantage of domain self-adaptability. © 2018 IEEE.},
author_keywords = {Differential evolution; Evolutionary algorithms; Link prediction},
keywords = {Artificial intelligence; Evolutionary algorithms; Optimization, Binary correlations; Correlation index; Differential Evolution; Differential evolution algorithms; Link prediction; Prediction performance; Self-adaptability; Similarity measure, Forecasting},
sponsors = {American Council on Science and Education},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Chan2018254,
author = {Chan, S.W. and Franzoni, V. and Mengoni, P. and Milani, A.},
title = {Context-Based Image Semantic Similarity for Prosthetic Knowledge},
journal = {Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018},
year = {2018},
pages = {254-258},
doi = {10.1109/AIKE.2018.00057},
art_number = {8527489},
note = {Conference of 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018 ; Conference Date: 26 September 2018 Through 28 September 2018; Conference Code:142285},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058231516&doi=10.1109%2fAIKE.2018.00057&partnerID=40&md5=fa2beb28e3b4f1c61182601ae4309a16},
abstract = {Textual information is concept-based information which is used for image representation, like captions, tags or comments. It can convey more concept-related meaning than low-level features. In this work, we will analyze the text connected to images (metadata, comments, tags, etc.) to extract a set of concepts, which can characterize the semantic context of the given image. We propose a context-based image similarity scheme for prosthetic knowledge by evaluating image similarity using the associated groups of concepts. The evaluation can be used in combination with different measures such as WordNet, Wikipedia, and other basic distance metrics to build the group distance comparison. Among semantic measures, web-based proximity measures (e.g. MC, Jaccard, Dice), which exploit statistical data provided by search engines, are particularly effective for similarity evaluation between concepts. Experiments are conducted on tagged images from Flickr repository. The results show that the proposed approach is adequate to measure the image concept similarity and the relationships among images with respect to human evaluation. The proposed methodology is able to reflect the collective notion of semantic similarity. © 2018 IEEE.},
author_keywords = {Collective knowledge; Context extraction; Image retrieval; Knowledge discovery; Semantic similarity; Web based proximity measures},
keywords = {Data mining; Image analysis; Image retrieval; Knowledge engineering; Prosthetics; Semantic Web; Semantics; Websites, Collective knowledge; Concept similarity; Context extractions; Image representations; Proximity measure; Semantic similarity; Similarity evaluation; Textual information, Search engines},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2018239,
author = {Franzoni, V. and Lepri, M. and Li, Y. and Milani, A.},
title = {Efficient Graph-Based Author Disambiguation by Topological Similarity in DBLP},
journal = {Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018},
year = {2018},
pages = {239-243},
doi = {10.1109/AIKE.2018.00054},
art_number = {8527486},
note = {Conference of 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018 ; Conference Date: 26 September 2018 Through 28 September 2018; Conference Code:142285},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058225352&doi=10.1109%2fAIKE.2018.00054&partnerID=40&md5=c5949b64745542ab66302f8d7260a980},
abstract = {In this work, we introduce a novel method for entity resolution author disambiguation in bibliographic networks. Such a method is based on a 2-steps network traversal using topological similarity measures for rating candidate nodes. Topological similarity is widely used in the Link Prediction application domain to assess the likelihood of an unknown link. A similarity function can be a good approximation for equality, therefore can be used to disambiguate, basing on the hypothesis that authors with many common co-authors are similar. Our method has experimented on a graph-based representation of the public DBLP Computer Science database. The results obtained are extremely encouraging regarding Precision, Accuracy, and Specificity. Further good aspects are the locality of the method for disambiguation assessment which avoids the need to know the global network, and the exploitation of only a few data, e.g. author name and paper title (i.e., co-authorship data). © 2018 IEEE.},
author_keywords = {Rewards margin; Termination condition},
keywords = {Graphic methods; Knowledge engineering, Candidate nodes; Entity resolutions; Graph-based representations; Link prediction; Rewards margin; Similarity functions; Termination condition; Topological similarity, Topology},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Mengoni2018234,
author = {Mengoni, P. and Milani, A. and Li, Y.},
title = {Multi-Term Semantic Context Elicitation from Collaborative Networks},
journal = {Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018},
year = {2018},
pages = {234-238},
doi = {10.1109/AIKE.2018.00053},
art_number = {8527485},
note = {Conference of 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018 ; Conference Date: 26 September 2018 Through 28 September 2018; Conference Code:142285},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058212185&doi=10.1109%2fAIKE.2018.00053&partnerID=40&md5=ae194716025c61622e20bbc64f298299},
abstract = {In this work we present an innovative approach to the semantic context elicitation among a set of terms. Topic and context elicitation using semantic features can be applied to query expansion, natural language processing, and multimedia retrieval. Different techniques rely on web objects to extract information considering the direct semantic relationship between the observed objects. In our approach we explore the Wikipedia collaborative network to extract the pairwise semantic chains. The terms that constitute all the pairwise chains will define the context in which the set of terms are immersed. Traversal, graph and Steiner tree analysis are evaluated by experts. Results are encouraging and experts agree that the Steiner tree analysis conveys additional semantic information about the relationship among the words in the context. © 2018 IEEE.},
author_keywords = {Heuristic search; Random walk; Semantic context; Steiner trees; Wikipedia},
keywords = {Heuristic algorithms; Knowledge engineering; Natural language processing systems; Semantics; Trees (mathematics), Heuristic search; Random Walk; Semantic context; Steiner trees; Wikipedia, Semantic Web},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti2018,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {Algebraic Crossover Operators for Permutations},
journal = {2018 IEEE Congress on Evolutionary Computation, CEC 2018 - Proceedings},
year = {2018},
doi = {10.1109/CEC.2018.8477867},
art_number = {8477867},
note = {Conference of 2018 IEEE Congress on Evolutionary Computation, CEC 2018 ; Conference Date: 8 July 2018 Through 13 July 2018; Conference Code:140374},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85056270191&doi=10.1109%2fCEC.2018.8477867&partnerID=40&md5=ed90c65021a99cc9416d713b4ac2488d},
abstract = {Crossover operators are very important tools in Evolutionary Computation. Here we are interested in crossovers for the permutation representation that find applications in combinatorial optimization problems such as the permutation flowshop scheduling and the traveling salesman problem. We introduce three families of permutation crossovers based on algebraic properties of the permutation space. In particular, we exploit the group and lattice structures of the space. A total of 14 new crossovers is provided. Algebraic and semantic properties of the operators are discussed, while their performances are investigated by experimentally comparing them with known permutation crossovers on standard benchmarks from four popular permutation problems. Three different experimental scenarios are considered and the results clearly validate our proposals. © 2018 IEEE.},
author_keywords = {Algebraic crossovers; Lattice operators; Permutation crossovers},
keywords = {Algebra; Calculations; Combinatorial optimization; Semantics, Algebraic crossovers; Algebraic properties; Combinatorial optimization problems; Lattice operators; Permutation crossovers; Permutation flow-shop scheduling; Permutation problems; Permutation representation, Traveling salesman problem},
sponsors = {IEEE; IEEE Computational Intelligence Society (CIS)},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@book{Franzoni2018143,
author = {Franzoni, V.},
title = {Autonomous hexapod robot with artificial vision and remote control by myo-electric gestures: The innovative implementation tale of gAItano},
journal = {Cyber-Physical Systems for Next-Generation Networks},
year = {2018},
pages = {143-162},
doi = {10.4018/978-1-5225-5510-0.ch007},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049822513&doi=10.4018%2f978-1-5225-5510-0.ch007&partnerID=40&md5=60fbf69a2b6128cf52f9bca977352b75},
abstract = {The robot gAItano is an intelligent hexapod robot, able to move in an environment of unknown size and perform some autonomous actions. It uses the RoboRealm software in order to filter and recognize color blobs in its artificial vision stream, activate a script (VBScript in our case, or C or Python scripts) to compute decisions based on perception, and send the output to actuators using the PIP protocol. gAItano is thus a rational computerized agent: autonomous, or semi-autonomous when remote controlled; reactive; based on model (e.g., the line). gAItano moves in an environment which is partially observable, stochastic, semi-episodic, static, or semi-dynamic in case of human intervention, continuous both on perceptions and actions, multi-agent, because of human intervention that can have collaborative nature (e.g., when the human moves a block or the robot to increase his performance), or competitive (e.g., when the human moves a block or the robot to inhibit his performance). © 2018, IGI Global.},
keywords = {C (programming language); Computer vision; Intelligent robots; Multi agent systems; Remote control; Stochastic systems; Vision, Autonomous action; Color blobs; Hexapod robots; Human intervention; Multi agent; VBScript, Autonomous agents},
publisher = {IGI Global},
document_type = {Book Chapter},
source = {Scopus}
}
@article{Milani2018217,
author = {Milani, A. and Franzoni, V.},
title = {Soft behaviour modelling of user communities},
journal = {Journal of Theoretical and Applied Information Technology},
year = {2018},
volume = {96},
number = {1},
pages = {217-226},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85041124658&partnerID=40&md5=9337b0c888e3b9b4ddf4ce2b73868ce4},
abstract = {A soft modelling approach for describing behaviour in on-line user communities is introduced in this work. Behaviour models of individual users in dynamic virtual environments have been described in the literature in terms of timed transition automata; they have various drawbacks. Soft multi/agent behaviour automata are defined and proposed to describe multiple user behaviours and to recognise larger classes of user group histories, such as group histories which contain unexpected behaviours. The notion of deviation from the user community model allows defining a soft parsing process which assesses and evaluates the dynamic behaviour of a group of users interacting in virtual environments, such as e-learning and e-business platforms. The soft automaton model can describe virtually infinite sequences of actions due to multiple users and subject to temporal constraints. Soft measures assess a form of distance of observed behaviours by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed history as well as actions performed by unexpected users. The proposed model allows the soft recognition of user group histories also when the observed actions only partially meet the given behaviour model constraints. This approach is more realistic for real-time user community support systems, concerning standard boolean model recognition, when more than one user model is potentially available, and the extent of deviation from community behaviour models can be used as a guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an e-learning platform and plan compilation of the soft multi-agent behaviour automaton show the expressiveness of the proposed model. © 2005 – ongoing JATIT & LLS.},
author_keywords = {Automated planning; Community behaviour; Elearning; Timed transition automaton; User behaviour; User interaction},
publisher = {Asian Research Publishing Network},
document_type = {Article},
source = {Scopus}
}
@conference{Santucci2018,
author = {Santucci, V. and Spina, S. and Milani, A. and Biondi, G. and Di Bari, G.},
title = {Detecting hate speech for Italian language in social media},
journal = {CEUR Workshop Proceedings},
year = {2018},
volume = {2263},
doi = {10.4000/books.aaccademia.4799},
note = {Conference of 6th Evaluation Campaign of Natural Language Processing and Speech Tools for Italian. Final Workshop, EVALITA 2018 ; Conference Date: 12 December 2018 Through 13 December 2018; Conference Code:142825},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85058615767&doi=10.4000%2fbooks.aaccademia.4799&partnerID=40&md5=c89caa48cc1baac535863339cfffdd47},
abstract = {English. In this report we describe the hate speech detection system for the Italian language developed by a joint team of researchers from the two universities of Perugia (University for Foreigners of Perugia and University of Perugia). The experimental results obtained in the HaSpeeDe task of the Evalita 2018 evaluation campaign are analyzed. Finally, a suggestion for future research directions is provided in the conclusion. © 2018 CEUR-WS. All Rights Reserved.},
keywords = {Natural language processing systems; Social networking (online), Future research directions; Social media; Speech detection, Speech recognition},
sponsors = {CELI; Google Research, ELRA},
publisher = {CEUR-WS},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2018307,
author = {Baioletti, M. and Belli, V. and Di Bari, G. and Poggioni, V.},
title = {Neural Random Access Machines Optimized by Differential Evolution},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2018},
volume = {11298 LNAI},
pages = {307-319},
doi = {10.1007/978-3-030-03840-3_23},
note = {Conference of 17th Conference of the Italian Association for Artificial Intelligence, AI*IA 2018 ; Conference Date: 20 November 2018 Through 23 November 2018; Conference Code:221299},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85057425969&doi=10.1007%2f978-3-030-03840-3_23&partnerID=40&md5=a08f419c7270706a313b4508dfca409b},
abstract = {Recently a research trend of learning algorithms by means of deep learning techniques has started. Most of these are different implementations of the controller-interface abstraction: they use a neural controller as a “processor" and provide different interfaces for input, output and memory management. In this trend, we consider of particular interest the Neural Random-Access Machines, called NRAM, because this model is also able to solve problems which require indirect memory references. In this paper we propose a version of the Neural Random-Access Machines, where the core neural controller is trained with Differential Evolution meta-heuristic instead of the usual backpropagation algorithm. Some experimental results showing that this approach is effective and competitive are also presented. © 2018, Springer Nature Switzerland AG.},
author_keywords = {Differential Evolution; Neural networks; NRAM},
keywords = {Artificial intelligence; Backpropagation algorithms; Controllers; Deep learning; Evolutionary algorithms; Learning algorithms; Neural networks; Optimization, Controller interfaces; Differential Evolution; Learning techniques; Memory management; Memory references; Neural controller; NRAM; Random access machines, Random access storage},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2018436,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {Learning bayesian networks with algebraic differential evolution},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2018},
volume = {11102 LNCS},
pages = {436-448},
doi = {10.1007/978-3-319-99259-4_35},
note = {Conference of 15th International Conference on Parallel Problem Solving from Nature, PPSN 2018 ; Conference Date: 8 September 2018 Through 12 September 2018; Conference Code:217819},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053534758&doi=10.1007%2f978-3-319-99259-4_35&partnerID=40&md5=619f28f5958e47b9b6f43481fbd3bdd0},
abstract = {In this paper we introduce DEBN, a novel evolutionary algorithm for learning the structure of a Bayesian Network. DEBN is an instantiation of the Algebraic Differential Evolution which is designed and applied to a particular (product) group whose elements encode all the Bayesian Networks of a given set of random variables. DEBN has been experimentally investigated on a set of standard benchmarks and its effectiveness is compared with BFO-B, a recent and effective bacterial foraging algorithm for Bayesian Network learning. The experimental results show that DEBN largely outperforms BFO-B, thus validating our algebraic approach as a viable solution for learning Bayesian Networks. © 2018, Springer Nature Switzerland AG.},
author_keywords = {Algebraic Differential Evolution; Bayesian Networks Learning},
keywords = {Algebra; Evolutionary algorithms; Learning algorithms; Optimization; Problem solving, Algebraic approaches; Bacterial foraging algorithm; Bayesian network learning; Differential Evolution; Learning Bayesian networks; Viable solutions, Bayesian networks},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Mengoni2018414,
author = {Mengoni, P. and Milani, A. and Li, Y.},
title = {Community graph elicitation from students’ interactions in virtual learning environments},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2018},
volume = {10962 LNCS},
pages = {414-425},
doi = {10.1007/978-3-319-95168-3_28},
note = {Conference of 18th International Conference on Computational Science and Its Applications, ICCSA 2018 ; Conference Date: 2 July 2018 Through 5 July 2018; Conference Code:215639},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049891996&doi=10.1007%2f978-3-319-95168-3_28&partnerID=40&md5=4735b65f413a1448a0a0d69c522b150e},
abstract = {In this work we introduce a novel graph-based approach to elicit students’ communities. Teaching, in the blended learning environment, is delivered as a mixture of online and offline activities. While the online activities can be tracked and analysed in the Virtual Learning Environment, the offline activities fall out of the educators’ control scope. In this educational setting, communications take place using side channels, such as the instant messaging applications and social network platform. Using our approach, the students’ groupings and social interactions can be elicited by analysing the student-system interactions. The co-occurrence of interactions among the students give information about their social connections. This conveys information useful to elicit the students’ interaction graph and the student communities contained in it. Students’ leader-follower community structure can be elicited starting from the interaction network. This can empower teachers to plan and revise their Learning Designs as well as to identify situations that need teacher’s intervention, e.g. students at risk of failing the exam and/or dropping the studies. © Springer International Publishing AG, part of Springer Nature 2018.},
author_keywords = {Community detection; Graph analysis; Modularity maximization; Student interactions},
keywords = {Computer aided instruction; Graphic methods; Students; Teaching, Blended learning environments; Community detection; Community structures; Educational settings; Graph analysis; Interaction networks; Student interactions; Virtual learning environments, E-learning},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Mengoni2018398,
author = {Mengoni, P. and Milani, A. and Li, Y.},
title = {Clustering students interactions in eLearning systems for group elicitation},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2018},
volume = {10962 LNCS},
pages = {398-413},
doi = {10.1007/978-3-319-95168-3_27},
note = {Conference of 18th International Conference on Computational Science and Its Applications, ICCSA 2018 ; Conference Date: 2 July 2018 Through 5 July 2018; Conference Code:215639},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85049884476&doi=10.1007%2f978-3-319-95168-3_27&partnerID=40&md5=eea6376e6b7e4c019e39ee8d82df11ff},
abstract = {In this work we introduce a novel Learning Analytics approach to identify students’ communities. The introduction of Learning Management Systems in higher education requires the educators to plan their Learning Design (LD) process with the online scenario in mind. We examined the blended learning environment where this process takes place in the Virtual Learning Environment. This allows the educators to track most of the students’ individual activities, but the communications may be excluded from tracking since the students can use side communications channels, such as face-to-face communication, instant messaging and social network platforms. Our approach, using the student-system interactions histories, helps to discover hidden relationships among the students. The elicited information about students’ groupings and social interactions’ evolution over time can be used by educators to adapt and improve their LD process, to find associations between students’ social interactions and their academic performance, as well as to promote team-based learning. © Springer International Publishing AG, part of Springer Nature 2018.},
author_keywords = {Cluster analysis; Hidden relationships identification; Learning analytics; Student interactions},
keywords = {Association reactions; Cluster analysis; Computer aided instruction; Online systems; Students, Academic performance; Blended learning environments; Communications channels; Face-to-face communications; Learning analytics; Learning management system; Student interactions; Virtual learning environments, E-learning},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani201829,
author = {Milani, A. and Rajdeep, N. and Mangal, N. and Mudgal, R.K. and Franzoni, V.},
title = {Sentiment extraction and classification for the analysis of users’ interest in tweets},
journal = {International Journal of Web Information Systems},
year = {2018},
volume = {14},
number = {1},
pages = {29-40},
doi = {10.1108/IJWIS-12-2016-0069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85046804174&doi=10.1108%2fIJWIS-12-2016-0069&partnerID=40&md5=5d3b0983b0a2f427a8c826d4908b75f8},
abstract = {Purpose: This paper aims to propose an approach for the analysis of user interest based on tweets, which can be used in the design of user recommendation systems. The extract topics are seen positively by the user. Design/methodology/approach: The proposed approach is based on the combination of sentiment extraction and classification analysis of tweet to extract the topic of interest. The proposed hybrid method is original. The topic extraction phase uses a method based on semantic distance in the WordNet taxonomy. Sentiment extraction uses NLPcore. Findings: The algorithm has been extensively tested using real tweets generated by 1,000 users. The results are quite encouraging and outperform state-of-the-art results and confirm the suitability of the approach combining sentiment and categorization for the topic of interest extraction. Research limitations/implications: The hybrid method combining sentiment extraction and classification for user positive topics represents a novel contribution with many potential applications. Practical implications: The functionality of positive topic extraction is very useful as a component in the design of a recommender system based on user profiling from Twitter user behaviors. Social implications: The application of the proposed method in short-text social network can be massive and beyond the applications in tweets. Originality/value: There are few works that have considered both sentiment analysis and classification to find out users’ interest. The algorithm has been extensively tested using real tweets generated by 1,000 users. The results are quite encouraging and outperform state-of-the-art results. © 2018, Emerald Publishing Limited.},
author_keywords = {Sentiment analysis; Social media; Social network; Topic extraction; Twitter},
keywords = {Behavioral research; Recommender systems; Semantics; Sentiment analysis; Social networking (online), Classification analysis; Design/methodology/approach; Interest extractions; Semantic distance; Social implication; Social media; Topic extraction; Twitter, Data mining},
publisher = {Emerald Group Publishing Ltd.},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti2018271,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {Automatic algebraic evolutionary algorithms},
journal = {Communications in Computer and Information Science},
year = {2018},
volume = {830},
pages = {271-283},
doi = {10.1007/978-3-319-78658-2_20},
note = {Conference of 12th Italian Workshop on Artificial Life and Evolutionary Computation, WIVACE 2017 ; Conference Date: 19 September 2017 Through 21 September 2017; Conference Code:212649},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85045283757&doi=10.1007%2f978-3-319-78658-2_20&partnerID=40&md5=3f21682aaac374f5f8fcada3a8bef395},
abstract = {Motivated from the previously proposed algebraic framework for combinatorial optimization, here we introduce a novel formal languages-based perspective on discrete search spaces that allows to automatically derive algebraic evolutionary algorithms. The practical effect of the proposed approach is that the algorithm designer does not need to choose a solutions encoding and implement algorithmic procedures. Indeed, he/she only has to provide the group presentation of the discrete solutions of the problem at hand. Then, the proposed mechanism allows to automatically derive concrete implementations of a chosen evolutionary algorithms. Theoretical guarantees about the feasibility of the proposed approach are provided. © 2018, Springer International Publishing AG, part of Springer Nature.},
author_keywords = {Algebraic evolutionary algorithms; Combinatorial optimization; Formal language perspective},
keywords = {Algebra; Combinatorial mathematics; Combinatorial optimization; Formal languages, Algebraic framework; Algorithmic procedure; Group presentation; Search spaces; Theoretical guarantees, Evolutionary algorithms},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2018132,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {MOEA/DEP: An algebraic decomposition-based evolutionary algorithm for the multiobjective permutation flowshop scheduling problem},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2018},
volume = {10782 LNCS},
pages = {132-145},
doi = {10.1007/978-3-319-77449-7_9},
note = {Conference of 18th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2018 ; Conference Date: 4 April 2018 Through 6 April 2018; Conference Code:212329},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85044790254&doi=10.1007%2f978-3-319-77449-7_9&partnerID=40&md5=d3ec40878c9d1b95dc508d536d843db6},
abstract = {Algebraic evolutionary algorithms are an emerging class of meta-heuristics for combinatorial optimization based on strong mathematical foundations. In this paper we introduce a decomposition-based algebraic evolutionary algorithm, namely MOEA/DEP, in order to deal with multiobjective permutation-based optimization problems. As a case of study, MOEA/DEP has been experimentally validated on a multiobjective permutation flowshop scheduling problem (MoPFSP). In particular, the makespan and total flowtime objectives have been investigated. Experiments have been held on a widely used benchmark suite, and the obtained results have been compared with respect to the state-of-the-art Pareto fronts for MoPFSP. The experimental results have been analyzed by means of two commonly used performance metrics for multiobjective optimization. The analysis clearly shows that MOEA/DEP reaches new state-of-the-art results for the considered benchmark. © Springer International Publishing AG, part of Springer Nature 2018.},
author_keywords = {Algebraic evolutionary algorithms; Multiobjective optimization; Permutation Flowshop Scheduling Problem},
keywords = {Algebra; Combinatorial optimization; Multiobjective optimization; Scheduling, Algebraic decomposition; Benchmark suites; Mathematical foundations; Meta heuristics; Optimization problems; Performance metrics; Permutation flowshop scheduling problems; State of the art, Evolutionary algorithms},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2018401,
author = {Baioletti, M. and Di Bari, G. and Poggioni, V. and Tracolli, M.},
title = {Can differential evolution be an efficient engine to optimize neural networks?},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2018},
volume = {10710 LNCS},
pages = {401-413},
doi = {10.1007/978-3-319-72926-8_33},
note = {Conference of 3rd International Conference on Machine Learning, Optimization, and Big Data, MOD 2017 ; Conference Date: 14 September 2017 Through 17 September 2017; Conference Code:209059},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85039443726&doi=10.1007%2f978-3-319-72926-8_33&partnerID=40&md5=4ae56ccdfb784863e7f1069d0540647b},
abstract = {In this paper we present an algorithm that optimizes artificial neural networks using Differential Evolution. The evolutionary algorithm is applied according the conventional neuroevolution approach, i.e. to evolve the network weights instead of backpropagation or other optimization methods based on backpropagation. A batch system, similar to that one used in stochastic gradient descent, is adopted to reduce the computation time. Preliminary experimental results are very encouraging because we obtained good performance also in real classification dataset like MNIST, that are usually considered prohibitive for this kind of approach. © Springer International Publishing AG 2018.},
keywords = {Artificial intelligence; Backpropagation; Backpropagation algorithms; Big data; Classification (of information); Evolutionary algorithms; Learning systems; Neural networks; Stochastic systems, Batch systems; Computation time; Differential Evolution; Network weights; Neuro evolutions; Optimization method; Stochastic gradient descent, Optimization},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2017,
author = {Franzoni, V. and Chiancone, A. and Milani, A.},
title = {A Multistrain Bacterial Diffusion Model for Link Prediction},
journal = {International Journal of Pattern Recognition and Artificial Intelligence},
year = {2017},
volume = {31},
number = {11},
doi = {10.1142/S0218001417590248},
art_number = {1759024},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85020276588&doi=10.1142%2fS0218001417590248&partnerID=40&md5=8fd114a8e6fea6cbb1d075fd622ded6d},
abstract = {Topological link prediction is the task of assessing the likelihood of new future links based on topological properties of entities in a network at a given time. In this paper, we introduce a multistrain bacterial diffusion model for link prediction, where the ranking of candidate links is based on the mutual transfer of bacteria strains via physical social contact. The model incorporates parameters like efficiency of the receiver surface, reproduction rate and number of social contacts. The basic idea is that entities continuously infect their neighborhood with their own bacteria strains, and such infections are iteratively propagated on the social network over time. The probability of transmission can be evaluated in terms of strains, reproduction, previous transfer, surface transfer efficiency, number of direct social contacts i.e. neighbors, multiple paths between entities. The value of the mutual strains of infection between a pair of entities is used to rank the potential arcs joining the entity nodes. The proposed multistrain diffusion model and mutual-strain infection ranking technique have been implemented and tested on widely accepted social network data sets. Experiments show that the MSDM-LP and mutual-strain diffusion ranking technique outperforms state-of-the-art algorithms for neighbor-based ranking. © 2017 The Author(s).},
author_keywords = {bacterial diffusion; complex networks; Link prediction; MSDM-LP; nature-inspired computation; ranking algorithms; social network analysis},
keywords = {Bacteria; Complex networks; Efficiency; Forecasting; Iterative methods; Social networking (online); Topology, Link prediction; MSDM-LP; Ranking algorithm; Ranking technique; Social contacts; State-of-the-art algorithms; Surface transfer; Topological properties, Diffusion},
publisher = {World Scientific Publishing Co. Pte Ltd},
document_type = {Article},
source = {Scopus}
}
@conference{Franzoni2017924,
author = {Franzoni, V. and Milani, A. and Vallverdú, J.},
title = {Emotional affordances in human-machine interactive planning and negotiation},
journal = {Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017},
year = {2017},
pages = {924-930},
doi = {10.1145/3106426.3109421},
note = {Conference of 16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 ; Conference Date: 23 August 2017 Through 26 August 2017; Conference Code:130536},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031028021&doi=10.1145%2f3106426.3109421&partnerID=40&md5=0ba6305c0917838131eef1c88a9c4c26},
abstract = {Emotional affordances represent a recently introduced concept which model all the mechanisms used to collect/transmit emotional meaning in the context of human machine interaction. In this work, we introduce and formally define the cognitive role of emotional affordances in a collaboration human-machine dialogue as tools for triggering or recognizing planning-based activities of delegation, goal negotiation, state acquisition, plan prioritization, taking place with the interaction partner. The presented formal model is grounded in an emergency scenario where reacting to emotional affordances or transmitting an emotional content is instrumental to reach the goal of an effective collaborative response. The implementation issues of generation and recognition of emotional affordance are also discussed. © 2017 ACM.},
author_keywords = {Affective computing; Emotion recognition; Emotional affordance; Human-machine interaction; Interactive planning},
keywords = {Data mining; Human computer interaction; Man machine systems, Affective Computing; Affordances; Emotion recognition; Human machine interaction; Interactive planning, Speech recognition},
sponsors = {ACM SIGART; IEEE Computer Society Technical Committee on Intelligent Informatics (TCII); Web Intelligence Consortium (WIC)},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2017953,
author = {Franzoni, V. and Milani, A. and Biondi, G.},
title = {SEMO: A semantic model for emotion recognition in web objects},
journal = {Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017},
year = {2017},
pages = {953-958},
doi = {10.1145/3106426.3109417},
note = {Conference of 16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 ; Conference Date: 23 August 2017 Through 26 August 2017; Conference Code:130536},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031022776&doi=10.1145%2f3106426.3109417&partnerID=40&md5=ae2f9875ad087c7984fa0363c2c5b22a},
abstract = {In this work, we present SEMO, a Semantic Model for Emotion Recognition, which enables users to detect and quantify the emotional load related to basic emotions hidden in short, emotionally rich sentences (e.g. news titles, tweets, captions). The idea of assessing the semantic similarity of concepts by looking at the occurrences and co-occurrences of terms describing them in pages indexed by a search engine can be directly extended to emotions, and to the words expressing them in different languages. The emotional content associated to a particular emotion for a term can thus be estimated using webbased similarity measures, e.g. Confidence, PMI, NGD and PMING, aggregating the distance computed by a model of emotions, e.g. Ekman, Plutchik and Lovheim. Emotions are ranked based on their similarity to the analyzed text, describing each sentence through a vector of values of emotion load, which form the Vector Space Model for the chosen emotion model and similarity measures. The model is tested comparing experimental results to a ground truth in literature. SEMO takes care of both the phases of data collection and data analysis, to produce knowledge to be used in application domains such as social robots, recommender systems, and human-machine interactive systems. © 2017 ACM.},
author_keywords = {Affective data; Artificial intelligence; Emotion recognition; Semantic similarity measures; Sentiment analysis; Web document retrieval},
keywords = {Artificial intelligence; Data acquisition; Natural language processing systems; Search engines; Semantics; Speech recognition; Vector spaces, Affective data; Emotion recognition; Semantic similarity measures; Sentiment analysis; Web Document Retrieval, Semantic Web},
sponsors = {ACM SIGART; IEEE Computer Society Technical Committee on Intelligent Informatics (TCII); Web Intelligence Consortium (WIC)},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2017947,
author = {Franzoni, V. and Li, Y. and Mengoni, P.},
title = {A path-based model for emotion abstraction on facebook using sentiment analysis and taxonomy knowledge},
journal = {Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017},
year = {2017},
pages = {947-952},
doi = {10.1145/3106426.3109420},
note = {Conference of 16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 ; Conference Date: 23 August 2017 Through 26 August 2017; Conference Code:130536},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030996689&doi=10.1145%2f3106426.3109420&partnerID=40&md5=e5d99aa56c0f039cf7637af7083054d3},
abstract = {Each term in a short text can potentially convey emotional meaning. Facebook comments and shared posts often convey human biases, which play a pivotal role in information spreading and content consumption. Such bias is at the basis of humangenerated content, and capable of conveying contexts which shape the opinion of users through the social media flow of information. Starting from the observation that a separation in topic clusters, i.e. sub-contexts, spontaneously occur if evaluated by human common sense, this work introduces a process for automated extraction of sub-context in Facebook. Basing on emotional abstraction and valence, the automated extraction is exploited through a class of path-based semantic similarity measures and sentiment analysis. Experimental results are obtained using validated clustering techniques on such features, on the domain of information security, over a sample of over 9 million page users. An additional expert evaluation of clusters in tag clouds confirms that the proposed automated algorithm for emotional abstraction clusters Facebook comments compatibly with human common sense. The baseline methods rely on the robust notion of collective concept similarity. © 2017 ACM.},
author_keywords = {Artificial intelligence; Collective knowledge; Data mining; Emotional abstraction; Knowledge discovery; Semantic distance; Sentiment analysis; Word similarity},
keywords = {Abstracting; Artificial intelligence; Automation; Extraction; Natural language processing systems; Security of data; Semantics; Social networking (online), Collective knowledge; Emotional abstraction; Semantic distance; Sentiment analysis; Word similarity, Data mining},
sponsors = {ACM SIGART; IEEE Computer Society Technical Committee on Intelligent Informatics (TCII); Web Intelligence Consortium (WIC)},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2017931,
author = {Franzoni, V. and Poggioni, V.},
title = {Emotional book classification from book blurbs},
journal = {Proceedings - 2017 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017},
year = {2017},
pages = {931-938},
doi = {10.1145/3106426.3109422},
note = {Conference of 16th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2017 ; Conference Date: 23 August 2017 Through 26 August 2017; Conference Code:130536},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85030985955&doi=10.1145%2f3106426.3109422&partnerID=40&md5=b76492b80698bcc0ccab9ab9400cb72b},
abstract = {Knowing and predicting opinions of people is considered a strategic added value, interpreting the qualia i.e., the subjective nature of emotional content. The aim of this work is to study the feasibility of an emotion recognition and automated classification of books according to emotional tags, by means of a lexical and semantic analysis of book blurbs. A supervised learning approach is used to determine if a correlation exists between the characteristics of a book blurb and emotional icons associated to the book by users. In this paper the underlying idea of the system is presented, the preprocessing and features extraction phases are described and experimental results on the social network Zazie and its mood tags are discussed. © 2017 ACM.},
author_keywords = {Automated classification; Book classification; Emotion recognition; Machine learning; Sentiment analysis},
keywords = {Semantics; Speech recognition, Added values; Automated classification; Emotion recognition; Features extraction; Semantic analysis; Sentiment analysis; Supervised learning approaches, Learning systems},
sponsors = {ACM SIGART; IEEE Computer Society Technical Committee on Intelligent Informatics (TCII); Web Intelligence Consortium (WIC)},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti20171587,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {Algebraic Particle Swarm Optimization for the permutations search space},
journal = {2017 IEEE Congress on Evolutionary Computation, CEC 2017 - Proceedings},
year = {2017},
pages = {1587-1594},
doi = {10.1109/CEC.2017.7969492},
art_number = {7969492},
note = {Conference of 2017 IEEE Congress on Evolutionary Computation, CEC 2017 ; Conference Date: 5 June 2017 Through 8 June 2017; Conference Code:129053},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028506882&doi=10.1109%2fCEC.2017.7969492&partnerID=40&md5=003dfaa77f57b664cf9ec779b1a5fc68},
abstract = {Particle Swarm Optimization (PSO), though being originally introduced for continuous search spaces, has been increasingly applied to combinatorial optimization problems. In particular, we focus on the PSO applications to permutation problems. As far as we know, the most popular PSO variants that produce permutation solutions are those based on random key techniques. In this paper, after highlighting the main criticalities of the random key approach, we introduce a totally discrete PSO variant for permutation-based optimization problems. The proposed algorithm, namely Algebraic PSO (APSO), simulates the original PSO design in permutations search space. APSO directly represents the particle positions and velocities as permutations. The APSO search scheme is based on a general algebraic framework for combinatorial optimization previously, and successfully, introduced in the context of discrete differential evolution schemes. The particularities of the PSO design scheme arouse new challenges for the algebraic framework: the non-commutativity of the velocity terms, and the rationale behind the PSO inertial move. Design solutions have been proposed for both the issues, and two APSO variants are provided. Experiments have been held to compare the performances of the APSO schemes with respect to the random key based PSO schemes in literature. Widely adopted benchmark instances of four popular permutation problems have been considered. The experimental results clearly show, with high statistical evidence, that APSO outperforms its competitors. © 2017 IEEE.},
keywords = {Algebra; Benchmarking; Combinatorial optimization; Evolutionary algorithms; Optimization, Algebraic framework; Combinatorial optimization problems; Design solutions; Discrete differential evolutions; Optimization problems; Particle position; Permutation problems; Statistical evidence, Particle swarm optimization (PSO)},
sponsors = {},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Dee2017176,
author = {Dee, H. and Cufi, X. and Milani, A. and Marian, M. and Poggioni, V. and Aubreton, O. and Rabionet, A.R. and Rowlands, T.},
title = {Playfully coding: Embedding computer science outreach in schools},
journal = {Annual Conference on Innovation and Technology in Computer Science Education, ITiCSE},
year = {2017},
volume = {Part F128680},
pages = {176-181},
doi = {10.1145/3059009.3059038},
note = {Conference of 2017 ACM Conference on Innovation and Technology in Computer Science Education, ITiCSE 2017 ; Conference Date: 3 July 2017 Through 5 July 2017; Conference Code:128680},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029492679&doi=10.1145%2f3059009.3059038&partnerID=40&md5=a739ed9ddc95d7ebca100813ce8c9d4f},
abstract = {This paper describes a framework for successful interaction between universities and schools. It is common for computing academics interested in outreach (computer science evangelism) to work with local schools, particularly in countries where the computing curriculum in K-12 is new or underdeveloped. However it is rare for these collaborations to be ongoing, and for resources created through these school-university links to be shared beyond the immediate neighborhood. We have achieved this, through shared resources, careful evaluation, and cross-country collaboration. The activities themselves are inspired by ideas from the Lifelong Kindergarten group at MIT, emphasizing playful exploration of computational concepts and interdisciplinary working. © 2017 Copyright held by the owner/author(s).},
author_keywords = {Computational thinking; Playful coding; School-University links},
keywords = {Education; Education computing; Engineering research; Societies and institutions, Computational thinkings; Computing curricula; Playful coding; School-University links; Shared resources, Engineering education},
sponsors = {ACM SIGCSE},
publisher = {Association for Computing Machinery},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Akarsh20171,
author = {Akarsh, S. and Kishor, A. and Niyogi, R. and Milani, A. and Mengoni, P.},
title = {Social cooperation in autonomous agents to avoid the tragedy of the commons},
journal = {International Journal of Agricultural and Environmental Information Systems},
year = {2017},
volume = {8},
number = {2},
pages = {1-19},
doi = {10.4018/IJAEIS.2017040101},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85016054582&doi=10.4018%2fIJAEIS.2017040101&partnerID=40&md5=9024b4b2fdbe83741c9ddb842a829b50},
abstract = {In this paper, we address the "Tragedy of the Commons" (TOC) problem for shared-resource systems by considering different types of behaviors of agents. On one extreme are self-interested agents while on the other one, agents are concerned about the welfare of the society. Algorithms to capture the different behaviors of the agents with and without interaction among the agents are proposed. An extensive experimental analysis for the different cases has been carried out as well as comparisons of our algorithms with an existing approach. Our study shows that if the agents are willing to sacrifice for some period of time, the sustainability of the society increases considerably. Copyright © 2017, IGI Global.},
author_keywords = {Cooperation; Eagerness; Tragedy of the commons},
keywords = {Hardware; Information systems, Cooperation; Eagerness; Experimental analysis; Self-interested agents; Shared resources; Social cooperations; Tragedy of the commons, Autonomous agents, algorithm; experimental study; sustainability},
publisher = {IGI Global},
document_type = {Article},
source = {Scopus}
}
@article{Bartoli201727,
author = {Bartoli, D. and Marcugini, S. and Milani, A. and Pambianco, F.},
title = {Completeness of the 95256-cap in PG(12, 4)},
journal = {Electronic Notes in Discrete Mathematics},
year = {2017},
volume = {57},
pages = {27-32},
doi = {10.1016/j.endm.2017.02.006},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85015387599&doi=10.1016%2fj.endm.2017.02.006&partnerID=40&md5=8b09918291d43079ffb80a46c8f88598},
abstract = {We describe an algorithm for testing the completeness of caps in PG(r,q), q even. It allowed us to check that the 95256-cap in PG(12,4) recently found by Fu el al. (see [Fu Q., R. Li, L. Guo and G. Xu, Large caps in projective space PG(r,4), Finite Fields Appl. 35 (2015), 231–246]) is complete. © 2017 Elsevier B.V.},
author_keywords = {caps; complete caps; Projective spaces},
publisher = {Elsevier B.V.},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti2017960,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {A new precedence-based ant colony optimization for permutation problems},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10593 LNCS},
pages = {960-971},
doi = {10.1007/978-3-319-68759-9_79},
note = {Conference of 11th International Conference on Simulated Evolution and Learning, SEAL 2017 ; Conference Date: 10 November 2017 Through 13 November 2017; Conference Code:203759},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85034224471&doi=10.1007%2f978-3-319-68759-9_79&partnerID=40&md5=4c8112744f6110ec8386c0e17940761b},
abstract = {In this paper we introduce ACOP, a novel ACO algorithm for solving permutation based optimization problems. The main novelty is in how ACOP ants construct a permutation by navigating the space of partial orders and considering precedence relations as solution components. Indeed, a permutation is built up by iteratively adding precedence relations to a partial order of items until it becomes a total order, thus the corresponding permutation is obtained. The pheromone model and the heuristic function assign desirability values to precedence relations. An ACOP implementation for the Linear Ordering Problem (LOP) is proposed. Experiments have been held on a large set of widely adopted LOP benchmark instances. The experimental results show that the approach is very competitive and it clearly outperforms previous ACO proposals for LOP. © Springer International Publishing AG 2017.},
author_keywords = {Ant colony optimization; Linear ordering problem; Partial orders; Permutations representation},
keywords = {Artificial intelligence; Benchmarking; Heuristic algorithms; Iterative methods; Optimization; Set theory, Heuristic functions; Linear ordering problems; Optimization problems; Partial order; Permutation problems; Permutations representation; Precedence relations; Solution components, Ant colony optimization},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2017717,
author = {Franzoni, V. and Li, Y. and Mengoni, P. and Milani, A.},
title = {Clustering facebook for biased context extraction},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10404},
pages = {717-729},
doi = {10.1007/978-3-319-62392-4_52},
note = {Conference of 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference Date: 3 July 2017 Through 6 July 2017; Conference Code:195069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027149767&doi=10.1007%2f978-3-319-62392-4_52&partnerID=40&md5=525b4c88f65fef764cf328f45f665c38},
abstract = {Facebook comments and shared posts often convey human biases, which play a pivotal role in information spreading and content consumption, where short information can be quickly consumed, and later ruminated. Such bias is nevertheless at the basis of human-generated content, and being able to extract contexts that does not amplify but represent such a bias can be relevant to data mining and artificial intelligence, because it is what shapes the opinion of users through social media. Starting from the observation that a separation in topic clusters, i.e. sub-contexts, spontaneously occur if evaluated by human common sense, especially in particular domains e.g. politics, technology, this work introduces a process for automated context extraction by means of a class of path-based semantic similarity measures which, using third party knowledge e.g. WordNet, Wikipedia, can create a bag of words relating to relevant concepts present in Facebook comments to topic-related posts, thus reflecting the collective knowledge of a community of users. It is thus easy to create human-readable views e.g. word clouds, or structured information to be readable by machines for further learning or content explanation, e.g. augmenting information with time stamps of posts and comments. Experimental evidence, obtained by the domain of information security and technology over a sample of 9M3k page users, where previous comments serve as a use case for forthcoming users, shows that a simple clustering on frequency-based bag of words can identify the main context words contained in Facebook comments identifiable by human common sense. Group similarity measures are also of great interest for many application domains, since they can be used to evaluate similarity of objects in term of the similarity of the associated sets, can then be calculated on the extracted context words to reflect the collective notion of semantic similarity, providing additional insights on which to reason, e.g. in terms of cognitive factors and behavioral patterns. © Springer International Publishing AG 2017.},
author_keywords = {Artificial intelligence; Collective knowledge; Data mining; Knowledge discovery; Semantic distance; Word similarity},
keywords = {Artificial intelligence; Extraction; Security of data; Semantics; Social networking (online), Collective knowledge; Experimental evidence; Information spreading; Semantic distance; Semantic similarity; Semantic similarity measures; Structured information; Word similarity, Data mining},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2017705,
author = {Baioletti, M. and Santucci, V.},
title = {Fitness landscape analysis of the permutation flowshop scheduling problem with total flow time criterion},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10404},
pages = {705-716},
doi = {10.1007/978-3-319-62392-4_51},
note = {Conference of 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference Date: 3 July 2017 Through 6 July 2017; Conference Code:195069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027146877&doi=10.1007%2f978-3-319-62392-4_51&partnerID=40&md5=5e213d53020d447670415f9378715638},
abstract = {This paper provides a fitness landscape analysis of the Permutation Flowshop Scheduling Problem considering the Total Flow Time criterion (PFSP-TFT). Three different landscapes, based on three neighborhood relations, are considered. The experimental investigations analyze aspects such as the smoothness and the local optima structure of the landscapes. To the best of our knowledge, this is the first landscape analysis for PFSP-TFT. © Springer International Publishing AG 2017.},
keywords = {Artificial intelligence; Computer science; Computers, Experimental investigations; Fitness landscape analysis; Landscape analysis; Local optima; Neighborhood relation; Permutation flowshop scheduling problems; Total flowtime, Scheduling},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2017651,
author = {Franzoni, V. and Milani, A.},
title = {Structural and semantic proximity in information networks},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10404},
pages = {651-666},
doi = {10.1007/978-3-319-62392-4_47},
note = {Conference of 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference Date: 3 July 2017 Through 6 July 2017; Conference Code:195069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85027105516&doi=10.1007%2f978-3-319-62392-4_47&partnerID=40&md5=b618679bcb59ba75a55d5e0d1535bebe},
abstract = {This research includes the investigation, design and experimentation of models and measures of semantic and structural proximity for knowledge extraction and link prediction. The aim is to measure, predict and elicit, in particular, data from social or collaborative sources of heterogeneous information. The general idea is to use the information about entities (i.e. users) and relationships in collaborative or social repositories as an information source to infer the semantic context, and relations among the heterogeneous multimedia objects of any kind to extract the relevant structural knowledge. Contexts can then be used to narrow the domains and improve the performances of tasks such as disambiguation of entities, query expansion, emotion recognition and multimedia retrieval, just to mention a few. There is thus the need for techniques able to produce results, even approximated, with respect to a given query, for ranking a set of promising candidates. Tools to reach the rich information already exist: web search engines, which results can be calculated with web-based proximity measures. Semantic proximity is used to compute attributes e.g. textual information. On the other hand, non-textual (i.e. structural, topological) information in collaborative or social repositories is used in contexts where the object is located. Both web-based and structural similarity measures can make profit from suboptimal results of computations. Which measure to use, and how to optimize the extraction and the utility of the extracted information, are the open issues that we address in our work. © Springer International Publishing AG 2017.},
author_keywords = {Collective knowledge; Data mining; Group similarity; Knowledge discovery; Semantic distance},
keywords = {Data mining; Extraction; Information services; Semantic Web; Semantics; Websites, Collective knowledge; Group similarity; Heterogeneous information; Information networks; Knowledge extraction; Multimedia Retrieval; Semantic distance; Structural similarity, Search engines},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Biondi2017719,
author = {Biondi, G. and Franzoni, V. and Poggioni, V.},
title = {A deep learning semantic approach to emotion recognition using the IBM watson bluemix alchemy language},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10406 LNCS},
pages = {719-729},
doi = {10.1007/978-3-319-62398-6_51},
note = {Conference of 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference Date: 3 July 2017 Through 6 July 2017; Conference Code:195069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026772560&doi=10.1007%2f978-3-319-62398-6_51&partnerID=40&md5=0d0fbe96c3959b5dc1d52e19bb5d8390},
abstract = {Sentiment analysis and emotion recognition are emerging research fields of research that aim to build intelligent systems able to recognize and interpret human emotions. Due to the applicability of these systems to almost all kinds of markets, also the interest of companies and industries is grown in an exponential way in the last years and a lot of frameworks for programming these systems are introduced. IBM Watson is one of the most famous and used: it offers, among others, a lot of services for Natural Language Processing. In spite of broad-scale multi-language services, most of functions are not available in a lot of “secondary” languages (like Italian). The main objective of this work is to demonstrate the feasibility of a translation-based approach to emotion recognition in texts written in “secondary” languages. We present a prototypical system using IBM Watson to extract emotions from Italian text by means of Bluemix Alchemy Language. Some preliminary results are shown and discussed in order to stress pro and cons of the approach. © Springer International Publishing AG 2017.},
author_keywords = {Affective Computing; Alchemy language; Artificial intelligence; Computer science; Deep learning; Emotion Recognition; IBM; Language translation; Machine learning; Semantics; SEMO; Sentiment Analysis; Watson},
keywords = {Artificial intelligence; Computer science; Data mining; Deep learning; Intelligent systems; Learning algorithms; Learning systems; Natural language processing systems; Semantics; Speech recognition, Affective Computing; Alchemy language; Emotion recognition; Language translation; SEMO; Sentiment analysis; Watson, Translation (languages)},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Riganelli2017692,
author = {Riganelli, M. and Franzoni, V. and Gervasi, O. and Tasso, S.},
title = {EmEx, a tool for automated emotive face recognition using convolutional neural networks},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10406 LNCS},
pages = {692-704},
doi = {10.1007/978-3-319-62398-6_49},
note = {Conference of 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference Date: 3 July 2017 Through 6 July 2017; Conference Code:195069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026755482&doi=10.1007%2f978-3-319-62398-6_49&partnerID=40&md5=5aed2dc1777efa5743c4c5cd25497fa9},
abstract = {The work described in this paper represents the study and the attempt to make a contribution to one of the most stimulating and promising sectors in the field of emotion recognition, which is health care management. Multidisciplinary studies in artificial intelligence, augmented reality and psychology stressed out the importance of emotions in communication and awareness. The intent is to recognize human emotions, processing images streamed in real-time from a mobile device. The adopted techniques involve the use of open source libraries of visual recognition and machine learning approaches based on convolutional neural networks (CNN). © Springer International Publishing AG 2017.},
author_keywords = {Emotion recognition; Face detection; Image; Machine learning CNN; Recognition},
keywords = {Artificial intelligence; Augmented reality; Convolution; Learning systems; Mobile devices; Neural networks; Speech recognition, Convolutional neural network; Emotion recognition; Health-care managements; Image; Machine learning approaches; Open-source libraries; Recognition; Visual recognition, Face recognition},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2017653,
author = {Franzoni, V. and Biondi, G. and Milani, A.},
title = {A web-based system for emotion vector extraction},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10406 LNCS},
pages = {653-668},
doi = {10.1007/978-3-319-62398-6_46},
note = {Conference of 17th International Conference on Computational Science and Its Applications, ICCSA 2017 ; Conference Date: 3 July 2017 Through 6 July 2017; Conference Code:195069},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026743083&doi=10.1007%2f978-3-319-62398-6_46&partnerID=40&md5=b96ef0e8bb53531f54293db95c636a45},
abstract = {The ability of assessing the affective information content is of increasing interest in applications of computer science, e.g. in human machine interfaces, recommender systems, social robots. In this project, the architecture of a semantic system of emotions is designed and implemented, to quantify the emotional content of short sentences by evaluating and aggregating the semantic proximity of each term in the sentence from the basic emotions defined in a psychological model of emotions (e.g. Ekman, Plutchick, Lovheim). Our model is parametric with respect to the semantic proximity measures, focusing on web-based proximity measures, where data needed to evaluate the proximity can be retrieved from search engines on the Web. To test the performances of the model, a software system has been developed to both collect the statistical data and perform the emotion analysis. The system automatizes the phases of sentence preprocessing, search engine query, results parsing, semantic proximity calculation and the final phase of ranking of emotions. © Springer International Publishing AG 2017.},
author_keywords = {Affective computing; Affective data; Emotion recognition; Semantic similarity measures; Web document retrieval},
keywords = {Semantic Web; Semantics; Software testing; Syntactics; Websites, Affective Computing; Affective data; Emotion recognition; Semantic similarity measures; Web Document Retrieval, Search engines},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti201765,
author = {Baioletti, M. and Capotorti, A.},
title = {An efficient probabilistic merging procedure applied to statistical matching},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10351 LNCS},
pages = {65-74},
doi = {10.1007/978-3-319-60045-1_9},
note = {Conference of 30th International Conference on Industrial, Engineering, and Other Applications of Applied Intelligent Systems, IEA/AIE 2017 ; Conference Date: 27 June 2017 Through 30 June 2017; Conference Code:193189},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026291605&doi=10.1007%2f978-3-319-60045-1_9&partnerID=40&md5=859a30228ab3f677b2b3855e15a0323f},
abstract = {We propose to use a recently introduced merging procedure for jointly inconsistent probabilistic assessments to the statistical matching problem. The merging procedure is based on an efficient L1 distance minimization through mixed-integer linear programming that results not only feasible but also meaningful for imprecise (lower-upper) probability evaluations elicitation. Significance of the method can be appreciated whenever among quantities (events) there are logical (structural) constraints and there are different sources of information. Statistical matching problem has these features and is characterized by a set of random (discrete) variables that cannot be jointly observed. Separate observations share some common variable and this, together with structural constraints, make sometimes inconsistent the estimates of probability occurrences. Even though estimates on statistical matching are mainly conditional probabilities, inconsistencies appear only on events with the same conditioning, hence the correction procedure can be easily reduced to unconditional cases and the aforementioned procedure applied. © Springer International Publishing AG 2017.},
author_keywords = {L1 constrained minimization; Mixed integer programming; Probabilistic merging; Statistical matching},
keywords = {Constrained optimization; Intelligent systems; Merging; Probability; Statistics, Conditional probabilities; Constrained minimization; Mixed integer linear programming; Mixed integer programming; Probabilistic assessments; Probability evaluation; Sources of informations; Statistical matching, Integer programming},
sponsors = {International Society of Applied Intelligence (ISAI); The ANR (French National Research Agency) project ASPIQ (ASP Technologies for Querying Large-Scale Multisource Heterogeneous Web Information); University of Artois, France; University of Artois, France},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2017185,
author = {Milani, A. and Niyogi, R.},
title = {Automated web services composition with iterated services},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2017},
volume = {10352 LNAI},
pages = {185-194},
doi = {10.1007/978-3-319-60438-1_19},
note = {Conference of 23rd International Symposium on Methodologies for Intelligent Systems, ISMIS 2017 ; Conference Date: 26 June 2017 Through 29 June 2017; Conference Code:193509},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85021972637&doi=10.1007%2f978-3-319-60438-1_19&partnerID=40&md5=bd698e000ad2885d382e056427361ebe},
abstract = {In the last decade there has been a proliferation of web services based application systems. In some applications (e.g., e-commerce, weather forecast) a web service is invoked many times with different actual parameters to obtain a composed service. In this paper we introduce the notion of iterated services that are obtained from given atomic services by iteration. The iterated services provide compact and elegant solutions to such complex composition problems that are unsolvable using the existing approaches. We define a new service dependency graph model to capture web services with sets of objects as input/output. We give a translation of the web services composition problem to a planning problem. Finally, we transform a plan to a composed web service. We have implemented our approach using the BlackBox planner. © Springer International Publishing AG 2017.},
author_keywords = {Automated planning; Iterated services; Web services composition},
keywords = {Intelligent systems; Iterative methods; Problem solving; Weather forecasting; Websites, Atomic services; Automated planning; Black boxes; Complex compositions; Iterated services; New services; Planning problem; Web services composition, Web services},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Biondi2016327,
author = {Biondi, G. and Franzoni, V. and Li, Y. and Milani, A.},
title = {Web-based similarity for emotion recognition in web objects},
journal = {Proceedings - 9th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2016},
year = {2016},
pages = {327-332},
doi = {10.1145/2996890.3007883},
note = {Conference of 9th IEEE/ACM International Conference on Utility and Cloud Computing, UCC 2016 ; Conference Date: 6 December 2016 Through 9 December 2016; Conference Code:125320},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009113178&doi=10.1145%2f2996890.3007883&partnerID=40&md5=57d7f1329ff178ccb6185539c54d20c3},
abstract = {In this project we propose a new approach for emotion recognition using web-based similarity (e.g. confidence, PMI and PMING). We aim to extract basic emotions from short sentences with emotional content (e.g. news titles, tweets, captions), performing a web-based quantitative evaluation of semantic proximity between each word of the analyzed sentence and each emotion of a psychological model (e.g. Plutchik, Ekman, Lovheim). The phases of the extraction include: text preprocessing (tokenization, stop words, filtering), search engine automated query, HTML parsing of results (i.e. scraping), estimation of semantic proximity, ranking of emotions according to proximity measures. The main idea is that, since it is possible to generalize semantic similarity under the assumption that similar concepts co-occur in documents indexed in search engines, therefore also emotions can be generalized in the same way, through tags or terms that express them in a particular language, ranking emotions. Training results are compared to human evaluation, then additional comparative tests on results are performed, both for the global ranking correlation (e.g. Kendall, Spearman, Pearson) both for the evaluation of the emotion linked to each single word. Different from sentiment analysis, our approach works at a deeper level of abstraction, aiming to recognize specific emotions and not only the positive/negative sentiment, in order to predict emotions as semantic data. © 2016 ACM.},
author_keywords = {Affective data; Emotion extraction; Emotion recognition; Information retrieval; Semantic similarity measures},
keywords = {Cloud computing; Extraction; Information retrieval; Natural language processing systems; Search engines; Semantics; Speech recognition; Syntactics; Websites, Affective data; Emotion extractions; Emotion recognition; Level of abstraction; Psychological model; Quantitative evaluation; Semantic similarity; Semantic similarity measures, Semantic Web},
sponsors = {},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Santucci2016682,
author = {Santucci, V. and Baioletti, M. and Milani, A.},
title = {Algebraic differential evolution algorithm for the permutation flowshop scheduling problem with total flowtime criterion},
journal = {IEEE Transactions on Evolutionary Computation},
year = {2016},
volume = {20},
number = {5},
pages = {682-694},
doi = {10.1109/TEVC.2015.2507785},
art_number = {7352326},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84991688011&doi=10.1109%2fTEVC.2015.2507785&partnerID=40&md5=6eeac65875936eed3794431892809a3d},
abstract = {This paper introduces an original algebraic approach to differential evolution (DE) algorithms for combinatorial search spaces. An abstract algebraic differential mutation for generic combinatorial spaces is defined by exploiting the concept of a finitely generated group. This operator is specialized for the permutations space by means of an original randomized bubble sort algorithm. Then, a discrete DE algorithm is derived for permutation problems and it is applied to the permutation flowshop scheduling problem with the total flowtime criterion. Other relevant components of the proposed algorithm are: a crossover operator for permutations, a novel biased selection strategy, a heuristic-based initialization, and a memetic restart procedure. Extensive experimental tests have been performed on a widely accepted benchmark suite in order to analyze the dynamics of the proposed approach and to compare it with the state-of-theart algorithms. The experimental results clearly show that the proposed algorithm reaches state-of-the-art performances and, most remarkably, it is able to find some new best known results. Furthermore, the experimental analysis on the impact of the algorithmic components shows that the two main contributions of this paper, i.e., the discrete differential mutation and the biased selection operator, greatly contribute to the overall performance of the algorithm. © 2015 IEEE.},
author_keywords = {Algebraic differential mutation; Differential evolution (DE); Permutation flowshop scheduling; Permutations space},
keywords = {Algebra; Evolutionary algorithms; Optimization; Scheduling, Differential Evolution; Differential evolution algorithms; Differential mutations; Finitely generated groups; Permutation flow-shop scheduling; Permutation flowshop scheduling problems; Permutations space; State-of-the-art performance, Combinatorial mathematics},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Article},
source = {Scopus}
}
@article{Mancini2016301,
author = {Mancini, L. and Milani, A. and Poggioni, V. and Chiancone, A.},
title = {Self regulating mechanisms for network immunization},
journal = {AI Communications},
year = {2016},
volume = {29},
number = {2},
pages = {301-317},
doi = {10.3233/AIC-150693},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960441860&doi=10.3233%2fAIC-150693&partnerID=40&md5=0d4d6bc61e60961fefefe911f1b8b9a7},
abstract = {Immunization strategies are significant in many real scale-free networks, e.g. Internet or communication systems, to prevent virus infections. Several centralized and distributed strategies have been proposed in the last few years. They are efficient but they share the same major limitation: they need to know in advance the network topology and the size of the network or the number of nodes that must be immunized. These requirements make those strategies unsuitable for application to real and dynamic networks. In this paper, we propose an immunization strategy based on distributed autonomous entities that self-regulate their diffusion in the network where they are deployed. Experiments show that the proposed approach produces a population that is able to self regulate in many widely accepted benchmarks while achieving different target coverage rates. © 2016 - IOS Press and the authors. All rights reserved.},
author_keywords = {Network immunization; scale-free networks; Self Regulating strategy},
keywords = {Complex networks; Immunization; Viruses, Autonomous entities; Distributed strategies; Dynamic network; Network immunizations; Network topology; Self Regulating strategy; Target coverage; Virus infection, Computer viruses},
publisher = {IOS Press BV},
document_type = {Article},
source = {Scopus}
}
@article{Santucci2016269,
author = {Santucci, V. and Baioletti, M. and Milani, A.},
title = {Solving permutation flowshop scheduling problems with a discrete differential evolution algorithm},
journal = {AI Communications},
year = {2016},
volume = {29},
number = {2},
pages = {269-286},
doi = {10.3233/AIC-150695},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960350951&doi=10.3233%2fAIC-150695&partnerID=40&md5=eda926c64309cb5cd1be450df9134440},
abstract = {In this paper a new discrete Differential Evolution algorithm for the Permutation Flowshop Scheduling Problem with the total flowtime and makespan criteria is proposed. The core of the algorithm is the distance-based differential mutation operator defined by means of a new randomized bubble sort algorithm. This mutation scheme allows the Differential Evolution to directly navigate the permutations search space. Experiments were held on a well known benchmarks suite and they show that the proposal reaches very good performances compared to other state-of-the-art algorithms. The results are particularly satisfactory on the total flowtime criterion where also new upper bounds that improve on the state-of-the-art have been found. © 2016 - IOS Press and the authors. All rights reserved.},
author_keywords = {differential evolution; Permutation flowshop scheduling problem; permutation-based optimization},
keywords = {Optimization; Scheduling, Differential Evolution; Differential mutations; Discrete differential evolution algorithm; Discrete differential evolutions; Permutation flowshop scheduling problems; State of the art; State-of-the-art algorithms; Total flowtime, Evolutionary algorithms},
publisher = {IOS Press},
document_type = {Article},
source = {Scopus}
}
@conference{Milani201625,
author = {Milani, A. and Poggioni, V. and Queri, R.},
title = {Self regulating immunization strategy for high clustering networks},
journal = {Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015},
year = {2016},
volume = {2},
pages = {25-28},
doi = {10.1109/WI-IAT.2015.180},
art_number = {7397310},
note = {Conference of 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015 ; Conference Date: 6 December 2015 Through 9 December 2015; Conference Code:119425},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85028328451&doi=10.1109%2fWI-IAT.2015.180&partnerID=40&md5=b28c635747d8e728ca6dd3c6cd7cc7c5},
abstract = {In this paper, we propose a new network immunization strategy for high clustering networks based on distributed autonomous entities which self-regulate their diffusion in the network. The advantage of a Self Regulating approach is that it can be applied to decentralized, unknown and dynamic networks. This strategy has been tested on several widely accepted benchmarks, and preliminary results are presented and discussed. © 2015 IEEE.},
keywords = {Intelligent agents, Autonomous entities; Clustering networks; Dynamic network; Network immunization strategies, Immunization},
sponsors = {Association for Computing Machinery (ACM); DataSpark; IEEE; IEEE Computer Society; Memetic Computing Society; Web Intelligence Consortium (WIC)},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2016540,
author = {Franzoni, V. and Milani, A.},
title = {A pheromone-like model for semantic context extraction from collaborative networks},
journal = {Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015},
year = {2016},
volume = {2016-January},
pages = {540-547},
doi = {10.1109/WI-IAT.2015.21},
art_number = {7396860},
note = {Conference of 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015 ; Conference Date: 6 December 2015 Through 9 December 2015; Conference Code:119425},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85009061734&doi=10.1109%2fWI-IAT.2015.21&partnerID=40&md5=5a8452f2df1ab025c2c583b517fbfc9b},
abstract = {The extraction of semantic contexts is a relevant issue in information retrieval to provide high quality query results. This paper introduces the semantic context underlying a set of given input concepts as defined by the relevant multiple explanation paths connecting the input concepts in a collaborative network. A pheromone-like model based on this approach is introduced for the detection and the extraction of multiple paths of explanation between seed concepts. The exploration of the online collaborative network of explanation uses a heuristic driven random walk, based on semantic proximity measures. Random walks distribute pheromone on the traversed arcs used to evaluate the relevance of concepts in the multiple explanatory paths to be extracted. Experimental results obtained on accepted datasets and contexts extracted from the Wikipedia collaborative network show that the proposed algorithm can extract contexts with high relevance degree, which outperforms other methods. The approach has a general applicability and can be extended to other explanation-based online collaborative networks. © 2015 IEEE.},
author_keywords = {Heuristic search; Proximity measures; Semantic context; Web mining},
keywords = {Extraction; Heuristic algorithms; Intelligent agents; Random processes; Semantics, Collaborative network; Heuristic search; Model-based OPC; Multiple-path; Proximity measure; Query results; Semantic context; Web Mining, Semantic Web},
sponsors = {Association for Computing Machinery (ACM); DataSpark; IEEE; IEEE Computer Society; Memetic Computing Society; Web Intelligence Consortium (WIC)},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Chiancone2016135,
author = {Chiancone, A. and Franzoni, V. and Li, Y. and Markov, K. and Milani, A.},
title = {Leveraging zero tail in neighbourhood for link prediction},
journal = {Proceedings - 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology, WI-IAT 2015},
year = {2016},
pages = {135-139},
doi = {10.1109/WI-IAT.2015.129},
art_number = {7397440},
note = {Conference of 2015 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, WI-IAT Workshops 2015 ; Conference Date: 6 December 2015 Through 9 December 2015; Conference Code:119425},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84969234393&doi=10.1109%2fWI-IAT.2015.129&partnerID=40&md5=fb4359018735000e0c28b60d8cbf0922},
abstract = {For link prediction, Common Neighbours (CN) ranking measures allow to discover quality links between nodes in a social network, assessing the likelihood of a new link based on the neighbours frontier of the already existing nodes. A zero rank value is often given to a large number of pairs of nodes, which have no common neighbours, that instead can be potentially good candidates for a quality assessment. With the aim of improving the quality of the ranking for link prediction, in this work we propose a general technique to evaluate the likelihood of a linkage, iteratively applying a given ranking measure to the Quasi-Common Neighbours (QCN) of the node pair, i.e. iteratively considering paths between nodes, which include more than one traversing step. Experiments held on a number of datasets already accepted in literature show that QCNAA, our QCN measure derived from the well know Adamic-Adar (AA), effectively improves the quality of link prediction methods, keeping the prediction capability of the original AA measure. This approach, being general and usable with any CN measure, has many different applications, e.g. trust management, terrorism prevention, disambiguation in co-authorship networks. © 2015 IEEE.},
author_keywords = {Common neighbourhood; Link prediction; Ranking; Social network analysis},
keywords = {Forecasting; Intelligent agents; Iterative methods; Social networking (online), Co-authorship networks; Link prediction; Neighbourhood; Prediction capability; Quality assessment; Ranking; Terrorism prevention; Trust management, Quality control},
sponsors = {Association for Computing Machinery (ACM); DataSpark; IEEE; IEEE Computer Society; Memetic Computing Society; Web Intelligence Consortium (WIC)},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni20161280,
author = {Franzoni, V. and Milani, A. and Pallottelli, S. and Leung, C.H.C. and Li, Y.},
title = {Context-based image semantic similarity},
journal = {2015 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015},
year = {2016},
pages = {1280-1284},
doi = {10.1109/FSKD.2015.7382127},
art_number = {7382127},
note = {Conference of 12th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2015 ; Conference Date: 15 August 2015 Through 17 August 2015; Conference Code:119123},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84966651018&doi=10.1109%2fFSKD.2015.7382127&partnerID=40&md5=c3c780cf736e0436a381ccaca3b08275},
abstract = {In this work we propose Context-based Image Similarity, a scheme for discovering and evaluating image similarity in terms of the associated groups of concepts. Several semantic proximity/similarity among image concepts and different concept ontology - WordNet Distance, Wikipedia Distance, Flickr Distance, Confidence, Normalized Google Distance (NGD), Pointwise Mutual Information (PMI) and PMING, have been considered as elementary metrics for the context. Comparing to Content Based Image Retrieval (CBIR), which measures the image content similarities by low level features, the proposed Context-based Image Similarity outperformed CBIR in measuring the deep concept similarity and relationship of images. Experimental results, obtained in the domain of images semantic similarity using search engine based tag similarity, show the adequacy of the proposed approach in order to reflect the collective notion of semantic similarity. © 2015 IEEE.},
author_keywords = {collective knowledge; Context-based; data mining; image retrieval; knowleadge discovery; semantic},
keywords = {Content based retrieval; Data mining; Fuzzy systems; Image analysis; Image retrieval; Natural language processing systems; Semantics, collective knowledge; Concept similarity; Content-Based Image Retrieval; Context-based; knowleadge discovery; Normalized Google distances; Pointwise mutual information; Semantic similarity, Search engines},
sponsors = {},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti20162135,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {Linear Ordering Optimization with a Combinatorial Differential Evolution},
journal = {Proceedings - 2015 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015},
year = {2016},
pages = {2135-2140},
doi = {10.1109/SMC.2015.373},
art_number = {7379505},
note = {Conference of IEEE International Conference on Systems, Man, and Cybernetics, SMC 2015 ; Conference Date: 9 October 2015 Through 12 October 2015; Conference Code:119045},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960452670&doi=10.1109%2fSMC.2015.373&partnerID=40&md5=c371e319c93666c2cfb606e130c227cc},
abstract = {In this work, the Linear Ordering Problem (LOP) has been approached using a discrete algebraic-based Differential Evolution for the Linear Ordering Problem (LOP). The search space of LOP is composed by permutations of objects, thus it is possible to use some group theoretical concepts and methods. Indeed, the proposed algorithm is a combinatorial Differential Evolution scheme designed by exploiting the group structure of the LOP solutions in order to mimic the classical Differential Evolution behavior observed in continuous spaces. In particular, the proposed differential mutation operator allows to obtain both scaled and extended differences among LOP solutions represented by permutations. The performances have been evaluated over widely known LOP benchmark suites and have been compared to the state-of-The-Art results. © 2015 IEEE.},
author_keywords = {Combinatorial Optimization; Differential Evolution; Linear Ordering Problem},
keywords = {Combinatorial optimization; Cybernetics; Group theory; Optimization; Set theory, Benchmark suites; Continuous spaces; Differential Evolution; Differential evolution schemes; Differential mutations; Group structure; Linear ordering problems; State of the art, Evolutionary algorithms},
sponsors = {IEEE SMC Society; K C Wong Foundation},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Pallottelli2016281,
author = {Pallottelli, S. and Franzoni, V. and Milani, A.},
title = {Multi-path traces in semantic graphs for latent knowledge elicitation},
journal = {Proceedings - International Conference on Natural Computation},
year = {2016},
volume = {2016-January},
pages = {281-288},
doi = {10.1109/ICNC.2015.7378004},
art_number = {7378004},
note = {Conference of 11th International Conference on Natural Computation, ICNC 2015 ; Conference Date: 15 August 2015 Through 17 August 2015; Conference Code:118970},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960456612&doi=10.1109%2fICNC.2015.7378004&partnerID=40&md5=57a115a441c9a21733464a6c450d39e7},
abstract = {In this work an online collaborative semantic network is explored. The method used is based on multi-path traces for extracting latent contextual knowledge, which explores an unknown Semantic proximity measures based on search engines are uses as heuristics to navigate the collaborative network, in order to find multiple random paths representing traces between seed concepts. The exploration is driven by an online randomized walk informed by those heuristics, where the multiple traces model reinforces the most relevant explanatory paths using a pheromone-like approach to elicit latent contexts. Experiments have been held on Wikipedia and on the Word Similarity 353 dataset to evaluate the effectiveness of the method. The general methodology can be easily extended to other online collaborative graphs and to non-textual domains. © 2015 IEEE.},
author_keywords = {Heuristic Search; Proximity Measures; Web Mining},
keywords = {Data mining; Heuristic algorithms; Search engines; Semantics, Collaborative network; Contextual knowledge; General methodologies; Heuristic search; Proximity measure; Semantic network; Web Mining; Word similarity, Heuristic methods},
publisher = {IEEE Computer Society},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Chiancone20161075,
author = {Chiancone, A. and Milani, A. and Poggioni, V. and Pallottelli, S. and Madotto, A. and Franzoni, V.},
title = {A multistrain bacterial model for link prediction andrea chiancone},
journal = {Proceedings - International Conference on Natural Computation},
year = {2016},
volume = {2016-January},
pages = {1075-1079},
doi = {10.1109/ICNC.2015.7378141},
art_number = {7378141},
note = {Conference of 11th International Conference on Natural Computation, ICNC 2015 ; Conference Date: 15 August 2015 Through 17 August 2015; Conference Code:118970},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84960349396&doi=10.1109%2fICNC.2015.7378141&partnerID=40&md5=a49ffc414a40346337afb1f403fd1dd0},
abstract = {In this paper we introduce a novel model for link prediction in social network based on a quantitative growth and diffusion model of node features which are used to compute candidate links ranking. The model is inspired by the biological mechanisms which regulates bacteria reproduction and their transfer among subjects through physical contact. The basic idea is that nodes infect their neighborhood with their own bacteria strains, i.e. node identifiers, and the infections are iteratively propagated on the network over the time. The value of the mutual strains of infection in a pair of nodes is then used for ranking the potential arc joining the nodes. The iterative process of growth-infection and the mutual link ranking computation has been implemented and tested on widely accepted social network datasets. Experiments shows that the proposed model outperform state of the art ranking algorithms. © 2015 IEEE.},
author_keywords = {bacterial diffusion; Bio-Inspired Systems; Complex Networks; link prediction; nature inspired computation; ranking algorithm; social network analysis},
keywords = {Bacteria; Biomimetics; Cell proliferation; Complex networks; Forecasting; Social networking (online), Bacterial modeling; Bioinspired systems; Biological mechanisms; Iterative process; Link prediction; Physical contacts; Ranking algorithm; State of the art, Iterative methods},
publisher = {IEEE Computer Society},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2016123,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {An extension of algebraic differential evolution for the linear ordering problem with cumulative costs},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2016},
volume = {9921 LNCS},
pages = {123-133},
doi = {10.1007/978-3-319-45823-6_12},
note = {Conference of 14th International Conference on Parallel Problem Solving from Nature, PPSN 2016 ; Conference Date: 17 September 2016 Through 21 September 2016; Conference Code:181119},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84988484477&doi=10.1007%2f978-3-319-45823-6_12&partnerID=40&md5=61e677b1da86639c3ee362da13ee5e32},
abstract = {In this paper we propose an extension to the algebraic differential evolution approach for permutation based problems (DEP). Conversely from classical differential evolution, DEP is fully combinatorial and it is extended in two directions: new generating sets based on exchange and insertion moves are considered, and the case F > 1 is now allowed for the differential mutation operator. Moreover, also the crossover and selection operators of the original DEP have been modified in order to address the linear ordering problem with cumulative costs (LOPCC). The new DEP schemes are compared with the state-of-the-art LOPCC algorithms using a widely adopted benchmark suite. The experimental results show that DEP reaches competitive performances and, most remarkably, found 21 new best known solutions on the 50 largest LOPCC instances. © Springer International Publishing AG 2016.},
author_keywords = {Algebraic differential evolution; Linear ordering problem with cumulative costs; Permutations neighborhoods},
keywords = {Algebra; Costs; Evolutionary algorithms; Optimization; Set theory, Benchmark suites; Competitive performance; Cumulative cost; Differential Evolution; Differential mutations; Linear ordering problems; Permutations neighborhoods; Selection operators, Problem solving},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Mangal201612,
author = {Mangal, N. and Niyogi, R. and Milani, A.},
title = {Analysis of users’ interest based on tweets},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2016},
volume = {9790},
pages = {12-23},
doi = {10.1007/978-3-319-42092-9_2},
note = {Conference of 16th International Conference on Computational Science and Its Applications, ICCSA 2016 ; Conference Date: 4 July 2016 Through 7 July 2016; Conference Code:177679},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978306127&doi=10.1007%2f978-3-319-42092-9_2&partnerID=40&md5=cb8a1801ee6a02d41f7535c3e65c6d9a},
abstract = {Analysis of tweets would help in designing smart recommendation systems. Analysis of twitter messages is an interesting research area. Sentiment analysis of tweets has been done in some works. Another line of work is the classification of tweets into different categories. However, there are few works that have considered both sentiment analysis and classification to find out users’ interest. In this paper, we propose an approach that combines both sentiment analysis and classification. Thus we are able to extract the topic in which users are interested. We have implemented our algorithm using five lakhs of tweets and around one thousands of users. The results are quite encouraging. © Springer International Publishing Switzerland 2016.},
author_keywords = {Sentiment analysis; Social media; Twitter user},
keywords = {Social networking (online), Sentiment analysis; Social media; Twitter user, Data mining},
sponsors = {Beijing University of Post and Telecommunication, China; et al; NVidia Co., USA; Springer International Publishing AG, Switzerland; State Key Laboratory of Networking and Switching Technology, China; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Kanwar20161,
author = {Kanwar, S. and Niyogi, R. and Milani, A.},
title = {Discovering popular events on twitter},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2016},
volume = {9790},
pages = {1-11},
doi = {10.1007/978-3-319-42092-9_1},
note = {Conference of 16th International Conference on Computational Science and Its Applications, ICCSA 2016 ; Conference Date: 4 July 2016 Through 7 July 2016; Conference Code:177679},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978288244&doi=10.1007%2f978-3-319-42092-9_1&partnerID=40&md5=ddcdde4f524447be0ce1615faadfa1b6},
abstract = {Event detection in twitter is the process of discovering popular events using messages generated by the twitter users. Event detection is an interesting research topic. Tweets are focused and may contain short forms. The tweets are noisy because there may be personal messages by the user also. In this paper we propose an algorithm to find top k popular events using keywords contained in the tweets. This paper classifies the popular events into different categories and the timeline is provided for every event. The timeline is useful to check when the event was popular. Geotagging is also done to find where the event was popular. We have implemented the algorithm using 14,558 users and 5, 27,548 tweets over a period of 10 months (22 June, 2015 to 25 April, 2016). The results are quite promising. © Springer International Publishing Switzerland 2016.},
author_keywords = {Event detection; Social media; Twitter},
keywords = {Artificial intelligence; Computer science; Computers, Event detection; Geo-tagging; Research topics; Social media; Twitter, Social networking (online)},
sponsors = {Beijing University of Post and Telecommunication, China; et al; NVidia Co., USA; Springer International Publishing AG, Switzerland; State Key Laboratory of Networking and Switching Technology, China; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2016438,
author = {Franzoni, V. and Milani, A.},
title = {A semantic comparison of clustering algorithms for the evaluation of web-based similarity measures},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2016},
volume = {9790},
pages = {438-452},
doi = {10.1007/978-3-319-42092-9_34},
note = {Conference of 16th International Conference on Computational Science and Its Applications, ICCSA 2016 ; Conference Date: 4 July 2016 Through 7 July 2016; Conference Code:177679},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84978200101&doi=10.1007%2f978-3-319-42092-9_34&partnerID=40&md5=1f4495ef3fa4e5da9c8b624c25665967},
abstract = {The Internet explosion and the massive diffusion of mobile devices lead to the creation of a worldwide collaborative system, daily used by millions of users through search engines and application interfaces. New paradigms permit to calculate the similarity of terms using only the statistical information returned by a query, or from additional features; also old algorithms and measures have been applied to new domains and scopes, to efficiently find words clusters from the Web. The problem of evaluating such techniques and algorithms in new domains emerges, and highlights a still open field of experimentation. In this paper, preliminary tests have been held on different semantic proximity measures (average confidence, NGD, PMI, χ2, PMING Distance), and different clustering algorithms among the most used in literature have been compared (e.g. k-means, Expectation-Maximization, spectral clustering) for evaluating such measures. The suitability of the considered measures and methods to calculate the semantic proximity was verified at the state-of-art, and problems were identified, comparing the results of measurements to a ground truth provided by models of contextualized knowledge, clustering and human perception of semantic relations, which data are already studied in literature. © Springer International Publishing Switzerland 2016.},
author_keywords = {Clustering; Data mining; Information retrieval; Semantic evaluation; Semantic similarity},
keywords = {Algorithms; Data mining; Information retrieval; Maximum principle; Mobile devices; Search engines; Semantic Web; Semantics, Application interfaces; Clustering; Collaborative systems; Contextualized knowledge; Expectation - maximizations; Semantic evaluations; Semantic similarity; Statistical information, Clustering algorithms},
sponsors = {Beijing University of Post and Telecommunication, China; et al; NVidia Co., USA; Springer International Publishing AG, Switzerland; State Key Laboratory of Networking and Switching Technology, China; University of Perugia, Italy},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2015131,
author = {Franzoni, V. and Milani, A.},
title = {Semantic context extraction from collaborative networks},
journal = {Proceedings of the 2015 IEEE 19th International Conference on Computer Supported Cooperative Work in Design, CSCWD 2015},
year = {2015},
pages = {131-136},
doi = {10.1109/CSCWD.2015.7230946},
art_number = {7230946},
note = {Conference of 19th IEEE International Conference on Computer Supported Cooperative Work in Design, CSCWD 2015 ; Conference Date: 6 May 2015 Through 8 May 2015; Conference Code:115870},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84946542483&doi=10.1109%2fCSCWD.2015.7230946&partnerID=40&md5=fe0777d491e029f730469000694c3c03},
abstract = {A novel method for the automatic online extraction of contexts from collaborative explanation network is introduced. The method explore an unknown online collaborative network in order to find multiple explanatory paths between seed concepts. The exploration is driven by an online randomized walk informed by a heuristics based on semantic proximity measures. A pheromone-like model is then applied to the analysis of the relevance of concepts in multiple explanatory paths in order to extract the relevant contexts. Experiments held on the collaborative network Wikipedia and accepted datasets show that the proposed method is able to determine contexts with high degree of relevance which outperforms other methods. The methodology have general aim and it can be easily extended to other online collaborative networks and to non-textual domains. © 2015 IEEE.},
author_keywords = {Heuristic Search; Proximity Measures; Web Mining},
keywords = {Extraction; Heuristic algorithms; Interactive computer systems, Collaborative network; Degree of relevance; Heuristic search; Online extraction; Proximity measure; Semantic context; Web Mining; Wikipedia, Semantics},
sponsors = {IEEE Systems, Man, and Cybernetics Society; International Working Group on Computer Supported Cooperative Work in Design (CSCWD)},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Santucci20151479,
author = {Santucci, V. and Baioletti, M. and Milani, A.},
title = {An algebraic differential evolution for the linear ordering problem},
journal = {GECCO 2015 - Companion Publication of the 2015 Genetic and Evolutionary Computation Conference},
year = {2015},
pages = {1479-1480},
doi = {10.1145/2739482.2764693},
note = {Conference of 17th Genetic and Evolutionary Computation Conference, GECCO 2015 ; Conference Date: 11 July 2015 Through 15 July 2015; Conference Code:118007},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84959339754&doi=10.1145%2f2739482.2764693&partnerID=40&md5=5a33f496fd9cf46870dba1f9e615761e},
abstract = {In this paper we propose a discrete algebraic-based Differential Evolution for the Linear Ordering Problem (LOP). The search space of LOP is composed by permutations of objects, thus it is possible to use some group theoretical concepts and methods. Indeed, the proposed algorithm is a fully discrete Differential Evolution scheme and has been designed by exploiting the group structure of LOP solutions in order to mimic the classical Differential Evolution behavior observed in continuous numerical spaces. The performances have been evaluated over widely known LOP benchmark suites and have been compared to the state-of-the-art results.},
keywords = {Algebra; Evolutionary algorithms; Group theory; Set theory, Benchmark suites; Differential Evolution; Fully discrete; Group structure; Linear ordering problems; Search spaces; State of the art, Optimization},
sponsors = {ACM SIGEVO},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Deng2015,
author = {Deng, J.J. and Leung, C.H.C. and Milani, A. and Chen, L.},
title = {Emotional states associated with music: Classification, prediction of changes, and consideration in recommendation},
journal = {ACM Transactions on Interactive Intelligent Systems},
year = {2015},
volume = {5},
number = {1},
doi = {10.1145/2723575},
art_number = {4},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84967332968&doi=10.1145%2f2723575&partnerID=40&md5=776b6e30deb692db07d6683305959a89},
abstract = {We present several interrelated technical and empirical contributions to the problem of emotion-based music recommendation and show how they can be applied in a possible usage scenario. The contributions are (1) a new three-dimensional resonance-arousal-valence model for the representation of emotion expressed in music, together with methods for automatically classifying a piece of music in terms of this model, using robust regression methods applied to musical/acoustic features; (2) methods for predicting a listener's emotional state on the assumption that the emotional state has been determined entirely by a sequence of pieces of music recently listened to, using conditional random fields and taking into account the decay of emotion intensity over time; and (3) a method for selecting a ranked list of pieces of music that match a particular emotional state, using a minimization iteration method. A series of experiments yield information about the validity of our operationalizations of these contributions. Throughout the article, we refer to an illustrative usage scenario in which all of these contributions can be exploited, where it is assumed that (1) a listener's emotional state is being determined entirely by the music that he or she has been listening to and (2) the listener wants to hear additional music that matches his or her current emotional state. The contributions are intended to be useful in a variety of other scenarios as well. © 2015 ACM.},
author_keywords = {Affective computing; Conditional random fields; Emotional state; Music emotion recognition; Music recommendation; Musical emotion},
keywords = {Random processes; Regression analysis, Affective Computing; Conditional random field; Emotional state; Music emotions; Music recommendation; Musical emotion, Iterative methods},
publisher = {Association for Computing Machinery},
document_type = {Article},
source = {Scopus}
}
@conference{Baioletti201537,
author = {Baioletti, M. and Capotorti, A.},
title = {Efficient L1-based probability assessments correction: Algorithms and applications to belief merging and revision},
journal = {ISIPTA 2015 - Proceedings of the 9th International Symposium on Imprecise Probability: Theories and Applications},
year = {2015},
pages = {37-46},
note = {Conference of 9th International Symposium on Imprecise Probability: Theories and Applications, ISIPTA 2015 ; Conference Date: 20 July 2015 Through 24 July 2015; Conference Code:149223},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85026321501&partnerID=40&md5=9e3b7d54bf8c855d77a3ca58c65ed5f4},
abstract = {In this article we define a procedure which corrects an incoherent probability assessment on a finite domain by exploiting a geometric property of L1-distance (known also as Manhattan distance) and mixed integer programming. L1-distance minimization does not produce, in general, a unique solution but rather a corrected assessment that could result an imprecise probability model. We propose a correction method for the merging of two separate assessments whose direct juxtaposition could be incoherent, and for the revision of beliefs where the core of the assessment must remain unchanged. A prototypical example on antidoping analysis guides the reader through this article to explain the various procedures. © 2015 Proceedings of the 9th International Symposium on Imprecise Probability.},
author_keywords = {Coherence; Imprecise probability; Mixed-integer optimization; Probability merging and revision},
keywords = {Coherent light; Integer programming; Merging, Distance minimizations; Geometric properties; Imprecise probabilities; Imprecise probability models; Manhattan distance; Mixed integer optimization; Mixed integer programming; Probability assessments, Probability},
sponsors = {Dipartimento di Ingegneria E Geologia; Elsevier; Springer; Universita degli Studi 'G. d'Annunzio (Ud'A); Wiley},
publisher = {Society for Imprecise Probability: Theories and Applications, SIPTA},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Akarsh2015257,
author = {Akarsh, S. and Niyogi, R. and Milani, A.},
title = {Modeling socially synergistic behavior in autonomous agents},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2015},
volume = {9156},
pages = {257-272},
doi = {10.1007/978-3-319-21407-8_20},
note = {Conference of 15th International Conference on Computational Science and Its Applications, ICCSA 2015 ; Conference Date: 22 June 2015 Through 25 June 2015},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84982216567&doi=10.1007%2f978-3-319-21407-8_20&partnerID=40&md5=132b99a8941f463072f4fa4bca4675fe},
abstract = {The “Tragedy of the Commons” (TOC) is a problem in which the sustainability of the society (group of agents) reduces due to self-interested individual agents. Many areas of interest to society like climate change, fisheries management, preservation of rainforests exhibit this phenomenon. We have focused on understanding what is the degree of sacrifice that an agent can make so that the sustainability of the society can be extended. For this we first make a mathematical modeling of the TOC dilemma. Next we propose three types of algorithms corresponding to the different behaviors of the agents. First we assume that the agents are interested in their individual gains only. In this case the society survives for the least amount of time. In the second approach we assume that the agents make decisions based on the resource availability, individual gains or a combination of both. Here an agent’s behavior takes into account the welfare of the society to some extent. Thus now the society survives for a longer period of time compared to that in the previous case. In the third approach we define a measure of social awareness of the agents. This measure is indicative of the degree of sacrifice the agent is willing to make. Now the society performs considerably better than the second case. We have experimentally validated these results. Our study shows that if the agents are willing to sacrifice for some period of time, the sustainability of the society increases considerably. © Springer International Publishing Switzerland 2015.},
keywords = {Climate change; Software agents; Sustainable development, Fisheries management; Individual agent; Resource availability; Social awareness; Tragedy of the commons, Autonomous agents},
sponsors = {et al; Kyushu Sangyo University; Monash University; University of Basilicata; University of Calgary; University of Perugia},
publisher = {Springer Verlag},
document_type = {Article},
source = {Scopus}
}
@conference{Baioletti201580,
author = {Baioletti, M. and Milani, A. and Santucci, V.},
title = {A discrete differential evolution algorithm for multi-objective permutation flowshop scheduling},
journal = {CEUR Workshop Proceedings},
year = {2015},
volume = {1493},
pages = {80-87},
note = {Conference of 6th Italian Workshop on Planning and Scheduling, IPS 2015 ; Conference Date: 22 September 2015; Conference Code:117597},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84954319935&partnerID=40&md5=615a918cdbedb991d5ea799663678644},
abstract = {Real-world versions of the permutation flowshop scheduling problem (PFSP) have a variety of objective criteria to be optimized simultaneously. Multi-objective PFSP is also a relevant combinatorial multi-objective optimization problem. In this paper we propose a multiobjective evolutionary algorithm for PFSPs by extending the previously proposed discrete differential evolution scheme for single-objective PFSPs. The novelties of this proposal reside on the management of the evolved Pareto front and on the selection operator. A preliminary experimental evaluation has been conducted on three bi-objective PFSPs resulting from all the possible bi-objective combinations of the criteria makespan, total flowtime and total tardiness.},
keywords = {Algorithms; Multiobjective optimization; Optimization; Scheduling; Supply chain management, Discrete differential evolution algorithm; Discrete differential evolutions; Experimental evaluation; Multi objective evolutionary algorithms; Multi-objective optimization problem; Permutation flow-shop scheduling; Permutation flowshop scheduling problems; Selection operators, Evolutionary algorithms},
sponsors = {},
publisher = {CEUR-WS},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Niyogi2015399,
author = {Niyogi, R. and Milani, A.},
title = {Planning with sets},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2015},
volume = {9384},
pages = {399-409},
doi = {10.1007/978-3-319-25252-0_43},
note = {Conference of 22nd International Symposium on Methodologies for Intelligent Systems, ISMIS 2015 ; Conference Date: 21 October 2015 Through 23 October 2015; Conference Code:154659},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84951926661&doi=10.1007%2f978-3-319-25252-0_43&partnerID=40&md5=eda3d2f37ad91fe7b84705b5414d718f},
abstract = {In some real world applications like robotics, manufacturing, the same planning operator with single or multiple effects is instantiated to several objects. This is quite different from performing the same action (or plan) several times. In this paper we give an approach to construct an iterated form of these operators (actions). We call such actions iterated actions that are performed on sets of objects. In order to give a compact and formal specification of such actions, we define a new type of predicate called set predicate. We show that iterated actions on sets behave like classical planning actions. Thus any classical planner can be used to synthesize plans containing iterated actions. We formally prove the correctness of this approach. An implementable description of iterated actions is given in PDDL for an example domain. The implementations were carried out using the state-of-the-art BlackBox planner. © Springer International Publishing Switzerland 2015.},
author_keywords = {Classical planning; Iterated actions; PDDL; Set predicate},
keywords = {Intelligent systems, Black boxes; Classical planning; Iterated actions; Multiple effect; PDDL; Planning operators; Set predicate; State of the art, Robot programming},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2015408,
author = {Franzoni, V. and Leung, C.H.C. and Li, Y. and Mengoni, P. and Milani, A.},
title = {Set similarity measures for images based on collective knowledge},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2015},
volume = {9155},
pages = {408-417},
doi = {10.1007/978-3-319-21404-7_30},
note = {Conference of 15th International Conference on Computational Science and Its Applications, ICCSA 2015 ; Conference Date: 22 June 2015 Through 25 June 2015; Conference Code:157939},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84948956279&doi=10.1007%2f978-3-319-21404-7_30&partnerID=40&md5=70986d81dd4da58a0b4a72256689d758},
abstract = {This work introduces a new class of group similarity where different measures are parameterized with respect to a basic similarity defined on the elements of the sets. Group similarity measures are of great interest for many application domains, since they can be used to evaluate similarity of objects in term of the similarity of the associated sets, for example in multimedia collaborative repositories where images, videos and other multimedia are annotated with meaningful tags whose semantics reflects the collective knowledge of a community of users. The group similarity classes are formally defined and their properties are described and discussed. Experimental results, obtained in the domain of images semantic similarity by using search engine based tag similarity, show the adequacy of the proposed approach in order to reflect the collective notion of semantic similarity. © Springer International Publishing Switzerland 2015.},
author_keywords = {Collective knowledge; Data mining; Group similarity; Image retrieval; Knowledge discovery; Semantic distance},
keywords = {Data mining; Image retrieval; Semantics, Associated sets; Collective knowledge; Group similarity; Semantic distance; Semantic similarity; Similarity class; Similarity measure; Tag similarity, Search engines},
sponsors = {et al; Kyushu Sangyo University; Monash University; University of Basilicata; University of Calgary; University of Perugia},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Chiancone201521,
author = {Chiancone, A. and Franzoni, V. and Niyogi, R. and Milani, A.},
title = {Improving Link Ranking Quality by Quasi-Common Neighbourhood},
journal = {Proceedings - 15th International Conference on Computational Science and Its Applications, ICCSA 2015},
year = {2015},
pages = {21-26},
doi = {10.1109/ICCSA.2015.19},
art_number = {7166159},
note = {Conference of 15th International Conference on Computational Science and Its Applications, ICCSA 2015 ; Conference Date: 22 June 2015 Through 25 June 2015; Conference Code:115695},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84945976858&doi=10.1109%2fICCSA.2015.19&partnerID=40&md5=9c61b7f3e22f7b8fe5fd658b935cbb10},
abstract = {Most of the best performing link prediction ranking measures evaluate the common neighbourhood of a pair of nodes in a network, in order to assess the likelihood of a new link. On the other hand, the same zero rank value is given to node pairs with no common neighbourhood, which usually are a large number of potentially new links, thus resulting in very low quality overall link ranking in terms of average edit distance to the optimal rank. In this paper we introduce a general technique for improving the quality of the ranking of common neighbours-based measures. The proposed method iteratively applies any given ranking measure to the quasi-common neighbours of the node pair. Experiments held on widely accepted datasets show that QCNAA, a quasi-common neighbourhood measure derived from the well know Adamic-Adar (AA), generates rankings which generally improve the ranking quality, while maintaining the prediction capability of the original AA measure. © 2015 IEEE.},
author_keywords = {common neighbourhood; link prediction; ranking; social network analysis},
sponsors = {},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2014141,
author = {Franzoni, V. and Mencacci, M. and Mengoni, P. and Milani, A.},
title = {Semantic heuristic search in collaborative networks: Measures and contexts},
journal = {Proceedings - 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014},
year = {2014},
volume = {1},
pages = {141-148},
doi = {10.1109/WI-IAT.2014.27},
note = {Conference of 2014 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT 2014 ; Conference Date: 11 August 2014 Through 14 August 2014; Conference Code:108754},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84912574994&doi=10.1109%2fWI-IAT.2014.27&partnerID=40&md5=ef48c8b65700a221dbb93716a586e46a},
abstract = {Relating, connecting and navigating between concepts represent a major challenge for machine intelligence. On the other hand, collaborative repositories provide a large base of knowledge already filtered, structured, linked and meaningful from a human semantic point of view. Although these repositories are machine accessible, they have no formal explicit semantic tagging to help for automatic navigation in them. In this paper we present a randomized approach, based on Heuristic Semantic Walk (HSW) for searching a collaborative network in order to extract meaningful semantic chains between concepts. The method is based on the use of heuristics defined on semantic proximity measures, which can be easily computed from general search engines statistics. Information from multiple random chains can be used to compute semantic distances between the concepts, as well as to determine the underlying semantic context. The proposed method solves major issues posed by collaborative networks, such as large dimensions, high connectivity degree and dynamical evolution of online networks, which make classical search methods inefficient and unfeasible. In this study the HSW model has been experimented on Wikipedia. Tests held with the well known Word Sym353 benchmark for human evaluation show that the proposed model is comparable to best state-of-the-art results, while being the only web-based approach. Other potential applications range from query expansion, argumentation mining, and simulation of user navigation. © 2014 IEEE.},
keywords = {Heuristic algorithms; Heuristic methods; Petroleum reservoir evaluation; Search engines; Semantics, Automatic navigation; Collaborative network; Dynamical evolution; Explicit semantics; High connectivity; Machine intelligence; Randomized approach; Web-based approach, Semantic Web},
sponsors = {Association for Computing Machinery (ACM); et al.; IEEE Computer Society; Polish Mathematical Society; University of Warsaw; Web Intelligence Consortium (WIC)},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Cheng20142002,
author = {Cheng, V.C. and Leung, C.H.C. and Liu, J. and Milani, A.},
title = {Probabilistic aspect mining model for drug reviews},
journal = {IEEE Transactions on Knowledge and Data Engineering},
year = {2014},
volume = {26},
number = {8},
pages = {2002-2013},
doi = {10.1109/TKDE.2013.175},
art_number = {6678354},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904661038&doi=10.1109%2fTKDE.2013.175&partnerID=40&md5=94f81fe55c23bbf523a74da920a850cb},
abstract = {Recent findings show that online reviews, blogs, and discussion forums on chronic diseases and drugs are becoming important supporting resources for patients. Extracting information from these substantial bodies of texts is useful and challenging. We developed a generative probabilistic aspect mining model (PAMM) for identifying the aspects/topics relating to class labels or categorical meta-information of a corpus. Unlike many other unsupervised approaches or supervised approaches, PAMM has a unique feature in that it focuses on finding aspects relating to one class only rather than finding aspects for all classes simultaneously in each execution. This reduces the chance of having aspects formed from mixing concepts of different classes; hence the identified aspects are easier to be interpreted by people. The aspects found also have the property that they are class distinguishing: They can be used to distinguish a class from other classes. An efficient EM-algorithm is developed for parameter estimation. Experimental results on reviews of four different drugs show that PAMM is able to find better aspects than other common approaches, when measured with mean pointwise mutual information and classification accuracy. In addition, the derived aspects were also assessed by humans based on different specified perspectives, and PAMM was found to be rated highest. © 2013 IEEE.},
author_keywords = {aspect mining; Drug review; opinion mining; text mining; topic modeling},
keywords = {Classification (of information), Aspect mining; Extracting information; Opinion mining; Pointwise mutual information; Probabilistic aspects; Text mining; Topic Modeling; Unsupervised approaches, Data mining},
publisher = {IEEE Computer Society},
document_type = {Article},
source = {Scopus}
}
@article{Santucci2014161,
author = {Santucci, V. and Baioletti, M. and Milani, A.},
title = {A differential evolution algorithm for the permutation flowshop scheduling problem with total flow time criterion},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2014},
volume = {8672},
pages = {161-170},
doi = {10.1007/978-3-319-10762-2_16},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84921743021&doi=10.1007%2f978-3-319-10762-2_16&partnerID=40&md5=806d1b0b5628a546ff60433a153b0fa6},
abstract = {In this paper a new discrete Differential Evolution algorithm for the Permutation Flowshop Scheduling Problem with the total flowtime criterion is proposed. The core of the algorithm is the distance-based differential mutation operator defined by means of a new randomized bubble sort algorithm. This mutation scheme allows the Differential Evolution to directly navigate the permutations search space. Experiments were held on a well known benchmark suite and the results show that our proposal outperforms state-of-the-art algorithms on the majority of the problems. © Springer International Publishing Switzerland 2014.},
author_keywords = {Differential Evolution; Permutation Flowshop Scheduling Problem; Randomized Bubble Sort},
keywords = {Optimization; Scheduling; Problem solving, Benchmark suites; Bubble sort; Differential Evolution; Differential evolution algorithms; Differential mutations; Discrete differential evolution algorithm; Permutation flowshop scheduling problems; State-of-the-art algorithms, Evolutionary algorithms},
publisher = {Springer Verlag},
document_type = {Article},
source = {Scopus}
}
@conference{Franzoni201416,
author = {Franzoni, V. and Poggioni, V. and Zollo, F.},
title = {Can we infer book classification by blurbs?},
journal = {CEUR Workshop Proceedings},
year = {2014},
volume = {1127},
pages = {16-19},
note = {Conference of 5th Italian Information Retrieval Workshop, IIR 2014 ; Conference Date: 20 January 2014 Through 21 January 2014; Conference Code:108592},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84908293833&partnerID=40&md5=3e6924f9b4049525a826f555a124e6a9},
abstract = {The aim of this work is to study the feasibility of an automated classification of books in the social network Zazie by means of the lexical analysis of book blurbs. A supervised learning approach is used to determine if a correlation between the characteristics of a book blurb and the emotional icons associated to the book by the Zazie's users exists.},
keywords = {Automated classification; Lexical analysis; Supervised learning approaches},
sponsors = {},
publisher = {CEUR-WS},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2014798,
author = {Baioletti, M. and Chiancone, A. and Poggioni, V. and Santucci, V.},
title = {Towards a new generation ACO-based planner},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2014},
volume = {8584 LNCS},
number = {PART 6},
pages = {798-807},
doi = {10.1007/978-3-319-09153-2_59},
note = {Conference of 14th International Conference on Computational Science and Its Applications, ICCSA 2014 ; Conference Date: 30 June 2014 Through 3 July 2014; Conference Code:106576},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904911060&doi=10.1007%2f978-3-319-09153-2_59&partnerID=40&md5=0874a4f36889f779cd2e2dc364086a26},
abstract = {In this paper a new generation ACO-Based Planner, called ACOPlan 2013, is described. This planner is an enhanced version of ACOPlan, a previous ACO-Based Planner [3], which differs from the former in the search algorithm and in the implementation, now done on top of Downwards. The experimental results, even if are not impressive, are encouraging and confirm that ACO is a suitable method to find near optimal plan for propositional planning problems. © 2014 Springer International Publishing.},
keywords = {Computer science; Computers, Near-optimal; Propositional planning; Search Algorithms, Artificial intelligence},
sponsors = {Associacao Portuguesa de Investigacao Operacional; Kyushu Sangyo University (KSU); Monash University; Universidade do Minho; University of Basilicata; University of Perugia},
publisher = {Springer Verlag},
address = {Guimaraes},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2014327,
author = {Franzoni, V. and Mencacci, M. and Mengoni, P. and Milani, A.},
title = {Heuristics for semantic path search in Wikipedia},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2014},
volume = {8584 LNCS},
number = {PART 6},
pages = {327-340},
doi = {10.1007/978-3-319-09153-2_25},
note = {Conference of 14th International Conference on Computational Science and Its Applications, ICCSA 2014 ; Conference Date: 30 June 2014 Through 3 July 2014; Conference Code:106576},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84904900353&doi=10.1007%2f978-3-319-09153-2_25&partnerID=40&md5=1d42b5a8a91027f04f229392aba0f070},
abstract = {In this paper an approach based on Heuristic Semantic Walk (HSW) is presented, where semantic proximity measures among concepts are used as heuristics in order to guide the concept chain search in the collaborative network of Wikipedia, encoding problem-specific knowledge in a problem-independent way. Collaborative information and multimedia repositories over the Web represent a domain of increasing relevance, since users cooperatively add to the objects tags, label, comments and hyperlinks, which reflect their semantic relationships, with or without an underlying structure. As in the case of the so called Big Data, methods for path finding in collaborative web repositories require solving major issues such as large dimensions, high connectivity degree and dynamical evolution of online networks, which make the classical approach ineffective. Experiments held on a range of different semantic measures show that HSW lead to better results than state of the art search methods, and points out the relevant features of suitable proximity measures for the Wikipedia concept network. The extracted semantic paths have many relevant applications such as query expansion, synthesis of explanatory arguments, and simulation of user navigation. © 2014 Springer International Publishing.},
author_keywords = {collaborative networks; heuristics search; information retrieval; random walk; semantic networks; semantic similarity measures},
keywords = {Big data; Hypertext systems; Information retrieval; Semantics, Collaborative network; heuristics search; Random Walk; Semantic network; Semantic similarity measures, Semantic Web},
sponsors = {Associacao Portuguesa de Investigacao Operacional; Kyushu Sangyo University (KSU); Monash University; Universidade do Minho; University of Basilicata; University of Perugia},
publisher = {Springer Verlag},
address = {Guimaraes},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni201485,
author = {Franzoni, V. and Milani, A.},
title = {Heuristic semantic walk for concept chaining in collaborative networks},
journal = {International Journal of Web Information Systems},
year = {2014},
volume = {10},
number = {1},
pages = {85-103},
doi = {10.1108/IJWIS-11-2013-0031},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898080418&doi=10.1108%2fIJWIS-11-2013-0031&partnerID=40&md5=3ab587cdc9d1695305a4f14c3f1dbd8a},
abstract = {Purpose - In this work, a new general framework is proposed to guide navigation over a collaborative concept network, in order to discover paths between concepts. Finding semantic chains between concepts over a semantic network is an issue of great interest for many applications, such as explanation generation and query expansion. Collaborative concept networks over the web tend to have features such as large dimensions, high connectivity degree, dynamically evolution over the time, which represent special challenges for efficient graph search methods, since they result in huge memory requirements, high branching factors, unknown dimensions and high cost for accessing nodes. The paper aims to discuss these issues. Design/methodology/approach - The proposed framework is based on the novel notion of heuristic semantic walk (HSW). In the HSW framework, a semantic proximity measure among concepts, reflecting the collective knowledge embedded in search engines or other statistical sources, is used as a heuristic in order to guide the search in the collaborative network. Different search strategies, information sources and proximity measures, can be used to adapt HSW to the collaborative semantic network under consideration. Findings - Experiments held on the Wikipedia network and Bing search engine on a range of different semantic measures show that the proposed HSW approach with weighted randomized walk strategy outperforms state-of-the-art search methods. Originality/value - To the best of the authors' knowledge, the proposed HSW model is the first approach which uses search engine-based proximity measures as heuristic for semantic search. © Emerald Group Publishing Limited.},
author_keywords = {Advanced web applications; Collaborative networks; Communities on the web; Data mining; Heuristics search; Random walk; Semantic networks; Semantic similarity measures; Web mining; Web search and information extraction},
keywords = {Data mining; Information retrieval; Search engines; Semantics; Web crawler, Collaborative network; Heuristics search; Random Walk; Semantic network; Semantic similarity measures; WEB application; Web Mining; Web searches, Semantic Web},
publisher = {Emerald Group Publishing Ltd.},
document_type = {Article},
source = {Scopus}
}
@article{Chan2013506,
author = {Chan, S.W. and Leung, C.H.C. and Milani, A.},
title = {Knowledge extraction and mining in biomedical research using rule network model},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2013},
volume = {8211 LNAI},
pages = {506-515},
doi = {10.1007/978-3-319-02753-1_51},
note = {Conference of International Conference on Brain and Health Informatics, BHI 2013 ; Conference Date: 29 October 2013 Through 31 October 2013; Conference Code:102171},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84892926295&doi=10.1007%2f978-3-319-02753-1_51&partnerID=40&md5=de8f8c1e0d0b81e2d78eec6888aa0c09},
abstract = {Recent findings show that the quantity of published biomedical literature is increasing at a dramatic rate. Carrying out knowledge extraction from large amounts of research literature becomes a significant challenge. Here we introduce an automatic mechanism for processing such information and extracting meaningful medical knowledge from biomedical literature. Data mining and natural language processing (NLP) are applied in a novel model, called biomedical rule network model. Using this model, information and relationships among herbal materials and diseases, as well as the chemical constituents of herbs can be extracted automatically. Moreover, with the overlapping chemical constituents of herbs, alternative herbal materials can be discovered, and suggestions can be made to replace expensive treatment options with lower cost ones. © Springer International Publishing 2013.},
author_keywords = {Biomedical literature; Chemical constituent; Herb; Hypothesis; Natural language processing},
keywords = {Biomedical literature; Chemical constituents; Herb; Hypothesis; NAtural language processing, Extraction; Natural language processing systems, Data mining},
sponsors = {Gunma Prefecture Government; Maebashi City Government; Maebashi Convention Bureau; Web Intelligence Lab Inc.; Mitsuba Gakki Co. Ltd.},
address = {Maebashi},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni201383,
author = {Franzoni, V. and Poggioni, V. and Zollo, F.},
title = {Automated classification of book blurbs according to the emotional tags of the social network Zazie},
journal = {CEUR Workshop Proceedings},
year = {2013},
volume = {1096},
pages = {83-94},
note = {Conference of 1st International Workshop on Emotion and Sentiment in Social and Expressive Media, ESSEM 2013 ; Conference Date: 3 December 2013; Conference Code:110725},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84923016707&partnerID=40&md5=29a8c52dd25b858957a89db5152a2487},
abstract = {Sentiment Analysis and Opinion Mining are receiving increasing attention in many sectors because knowing and predicting opinions of people is considered a strategic added value. In the last years an increasing attention has also been devoted to Emotion Recognition, often by developing automated systems that can associate user's emotions to texts, music or artworks. Zazie is an Italian social network for readers that introduces a new dimension on book characterization, the emotional icon tagging. Each book, besides user's comments and reviews, can be tagged with special icons, the moods, that are emotional tags chosen by the users. The aim of this work is to study the feasibility of an automated classification of books in Zazie according to the emotional tags, by means of the lexical analysis of book blurbs. A supervised learning approach is used to determine if a correlation between the characteristics of a book blurb and the emotional icons associated to the book by the users exists.},
author_keywords = {Automated classification; Emotion recognition; Machine learning; Sentiment analysis},
keywords = {Artificial intelligence; Automation; Data mining; Learning systems; Social networking (online), Automated classification; Automated systems; Emotion recognition; Lexical analysis; New dimensions; Opinion mining; Sentiment analysis; Supervised learning approaches, Reviews},
sponsors = {},
publisher = {CEUR-WS},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti201337,
author = {Baioletti, M. and Petturiti, D. and Vantaggi, B.},
title = {Qualitative combination of independence models},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2013},
volume = {7958 LNAI},
pages = {37-48},
doi = {10.1007/978-3-642-39091-3_4},
note = {Conference of 12th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2013 ; Conference Date: 8 July 2013 Through 10 July 2013; Conference Code:98031},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880749185&doi=10.1007%2f978-3-642-39091-3_4&partnerID=40&md5=be5ddefb1d35e83585dbb710d6c2494d},
abstract = {We deal with the problem of combining sets of independence statements coming from different experts. It is known that the independence model induced by a strictly positive probability distribution has a graphoid structure, but the explicit computation and storage of the closure (w.r.t. graphoid properties) of a set of independence statements is a computational hard problem. For this, we rely on a compact symbolic representation of the closure called fast closure and study three different combination strategies of two sets of independence statements, working on fast closures. We investigate when the complete DAG representability of the given models is preserved in the combined one. © 2013 Springer-Verlag Berlin Heidelberg.},
author_keywords = {Combination of independence models; DAG; Fast closure; Graphoid; P-map},
keywords = {Artificial intelligence; Computer science; Computers, Combination strategies; Combining sets; Fast closure; Graphoid; Graphoid properties; Independence models; Representability; Symbolic representation, Probability distributions},
sponsors = {Artificial Intelligence Journal; Benelux Association for Artificial Intelligence (BNVKI); et al.; HUGIN Expert; Netherlands Organisation for Scientific Research (NWO); Utrecht University},
publisher = {Springer Verlag},
address = {Utrecht},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Leung2013657,
author = {Leung, C.H.C. and Li, Y. and Milani, A. and Franzoni, V.},
title = {Collective evolutionary concept distance based query expansion for effective web document retrieval},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2013},
volume = {7974 LNCS},
number = {PART 4},
pages = {657-672},
doi = {10.1007/978-3-642-39649-6_47},
note = {Conference of 13th International Conference on Computational Science and Its Applications, ICCSA 2013 ; Conference Date: 24 June 2013 Through 27 June 2013; Conference Code:97954},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880711690&doi=10.1007%2f978-3-642-39649-6_47&partnerID=40&md5=924a922c774a9f5d9182e5760a7750c4},
abstract = {In this work several semantic approaches to concept-based query expansion and re-ranking schemes are studied and compared with different ontology-based expansion methods in web document search and retrieval. In particular, we focus on concept-based query expansion schemes where, in order to effectively increase the precision of web document retrieval and to decrease the users' browsing time, the main goal is to quickly provide users with the most suitable query expansion. Two key tasks for query expansion in web document retrieval are to find the expansion candidates, as the closest concepts in web document domain, and to rank the expanded queries properly. The approach we propose aims at improving the expansion phase for better web document retrieval and precision. The basic idea is to measure the distance between candidate concepts using the PMING distance, a collaborative semantic proximity measure, i.e. a measure which can be computed using statistical results from a web search engine. Experiments show that the proposed technique can provide users with more satisfying expansion results and improve the quality of web document retrieval. © 2013 Springer-Verlag Berlin Heidelberg.},
author_keywords = {Concept distance; PMING distance; Precision and recall; Query expansion; Semantic similarity measures; Web document retrieval},
keywords = {Ontology; Search engines; Semantic Web; Semantics, Concept distance; PMING distance; Precision and recall; Query expansion; Semantic similarity measures; Web Document Retrieval, Information retrieval},
sponsors = {Ho CHi Minh City International University; Kyushu Sangyo University; Monash University; The Office of Naval Research; University of Basilicata; University of Perugia},
publisher = {Springer Verlag},
address = {Ho Chi Minh City},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2013643,
author = {Franzoni, V. and Milani, A.},
title = {Heuristic semantic walk: Browsing a collaborative network with a search engine-based heuristic},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2013},
volume = {7974 LNCS},
number = {PART 4},
pages = {643-656},
doi = {10.1007/978-3-642-39649-6_46},
note = {Conference of 13th International Conference on Computational Science and Its Applications, ICCSA 2013 ; Conference Date: 24 June 2013 Through 27 June 2013; Conference Code:97954},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880707624&doi=10.1007%2f978-3-642-39649-6_46&partnerID=40&md5=0e6038d517fecbce6e1788f97fc88b89},
abstract = {Path search between concepts over a semantic network is an issue of great interest for many applications, such as explanation generation and query expansion. In this study a new approach is proposed, to guide navigation over a collaborative concept network, in order to discover path between concepts. The method uses a semantic heuristic based on proximity measures, which reflects the collective knowledge embedded in search engines. The experiments held on the Wikipedia network and Bing search engine on a range of different semantic measures show that the proposed approach outperforms state of the art search methods. © 2013 Springer-Verlag Berlin Heidelberg.},
author_keywords = {Collaborative network; Data mining; Heuristics; Information extraction; Query expansion; Semantic similarity measures},
keywords = {Air navigation; Data mining; Heuristic methods; Information retrieval; Knowledge representation; Search engines; Semantics, Collaborative network; Heuristics; Proximity measure; Query expansion; Semantic measures; Semantic network; Semantic similarity measures; State of the art, Semantic Web},
sponsors = {Ho CHi Minh City International University; Kyushu Sangyo University; Monash University; The Office of Naval Research; University of Basilicata; University of Perugia},
publisher = {Springer Verlag},
address = {Ho Chi Minh City},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Gentili201213,
author = {Gentili, E. and Milani, A.},
title = {A model to summarize user action log files},
journal = {CEUR Workshop Proceedings},
year = {2012},
volume = {926},
pages = {13-17},
note = {Conference of Doctoral Consortium of the 12th Symposium of the Italian Association for Artificial Intelligence, AIxIA-DC 2012 ; Conference Date: 15 June 2012 Through 15 June 2012; Conference Code:101890},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84891751349&partnerID=40&md5=50ee527c19d7fe04afe29041a2953ff6},
abstract = {Social networks, web portals or e-learning platforms produce in general a large amount of data everyday, normally stored in its raw format in log file systems and databases. Such data can be condensed and summarized to improve reporting performance and reduce the system load. This data summarization reduces the amount of space that is required to store software data but produces, as a side effect, a decrease of their informative capability due to an information loss. In this work we study the problem of summarizing data obtained by the log systems of chronology-dependent applications with a lot of users. In particular, we present a method to reduce the data size, collapsing the descriptions of more events in a unique descriptor or in a smaller set of descriptors and pose the optimal summarization problem.},
keywords = {Data summarizations; Descriptors; E-learning platforms; Information loss; Large amounts; Side effect; Software data; System loads, Artificial intelligence; E-learning, Data reduction},
address = {Rome},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Franzoni2012442,
author = {Franzoni, V. and Milani, A.},
title = {PMING distance: A collaborative semantic proximity measure},
journal = {Proceedings - 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012},
year = {2012},
volume = {2},
pages = {442-449},
doi = {10.1109/WI-IAT.2012.226},
art_number = {6511606},
note = {Conference of 2012 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, IAT 2012 ; Conference Date: 4 December 2012 Through 7 December 2012; Conference Code:97231},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84878467978&doi=10.1109%2fWI-IAT.2012.226&partnerID=40&md5=04b6dc164fa836ba260807f9cfe96f20},
abstract = {One of the main problems that emerges in the classic approach to semantics is the difficulty in acquisition and maintenance of ontologies and semantic annotations. On the other hand, the flow of data and documents which are accessible from the Web is continuously fueled by the contribution of millions of users who interact digitally in a collaborative way. Search engines, continually exploring the Web, are therefore the natural source of information on which to base a modern approach to semantic annotation. A promising idea is that it is possible to generalize the semantic similarity, under the assumption that semantically similar terms behave similarly, and define collaborative proximity measures based on the indexing information returned by search engines. In this work PMING, a new collaborative proximity measure based on search engines, which uses the information provided by search engines, is introduced as a basis to extract semantic content. PMING is defined on the basis of the best features of other state-of-the-art proximity distances which have been considered. It defines the degree of relatedness between terms, by using only the number of documents returned as result for a query, then the measure dynamically reflects the collaborative change made on the web resources. Experiments held on popular collaborative and generalist engines (e.g. Flickr, Youtube, Google, Bing, Yahoo Search) show that PMING outperforms state-of-the-art proximity measures (e.g. Normalized Google Distance, Flickr Distance etc.), in modeling contexts, modeling human perception, and clustering of semantic associations. © 2012 IEEE.},
author_keywords = {data mining; information extraction; semantic similarity measure},
keywords = {Information Extraction; Normalized Google distances; Proximity measure; Semantic annotations; Semantic associations; Semantic content; Semantic similarity; Semantic similarity measures, Data mining; Intelligent agents; Natural language processing systems; Search engines; Semantics; World Wide Web, Semantic Web},
sponsors = {IEEE},
address = {Macau},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2012211,
author = {Baioletti, M. and Coletti, G. and Petturiti, D.},
title = {Weighted attribute combinations based similarity measures},
journal = {Communications in Computer and Information Science},
year = {2012},
volume = {299 CCIS},
number = {PART 3},
pages = {211-220},
doi = {10.1007/978-3-642-31718-7_22},
note = {Conference of 14th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2012 ; Conference Date: 9 July 2012 Through 13 July 2012; Conference Code:93506},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84868132492&doi=10.1007%2f978-3-642-31718-7_22&partnerID=40&md5=512a86bdff24a8204df17c7ed333bbeb},
abstract = {In this paper we introduce three parameterized similarity measures which take into account not only the single features of two objects under comparison, but also all the significant combinations of attributes. In this way a great expressive power can be achieved and field expert knowledge about relations among features can be encoded in the weights assigned to each combination. Here we consider only binary attributes and, in order to face the difficulty of weights' elicitation, we propose some effective techniques to learn weights from an already labelled dataset. Finally, a comparative study of classification power with respect to other largely used similarity indices is presented. © 2012 Springer-Verlag Berlin Heidelberg.},
author_keywords = {binary data; classification; similarity measure; weighted attribute combination},
keywords = {Binary attributes; Binary data; Classification power; Comparative studies; Data sets; Expert knowledge; Expressive power; Parameterized; Similarity indices; Similarity measure; Weighted attributes, Artificial intelligence; Classification (of information); Data processing; Knowledge based systems, Information management},
address = {Catania},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Nema2012528,
author = {Nema, J. and Niyogi, R. and Milani, A.},
title = {A framework for QoS based dynamic web services composition},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2012},
volume = {7335 LNCS},
number = {PART 3},
pages = {528-538},
doi = {10.1007/978-3-642-31137-6_40},
note = {Conference of 12th International Conference on Computational Science and Its Applications, ICCSA 2012 ; Conference Date: 18 June 2012 Through 21 June 2012; Conference Code:90945},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863972658&doi=10.1007%2f978-3-642-31137-6_40&partnerID=40&md5=4755b531eb097fcae957dfd05a8abce9},
abstract = {Web services composition based on quality of services have been recently studied by several researchers. Service composition with minimum communication cost has been well studied for service overlay networks. However there are very few optimization algorithms available which considers more than one objective. Finding a solution that optimizes all the objectives is nontrivial. In multi-objective optimization problem, the solution can be given in such a way that it fulfills the requirements of the user without making much sacrifice from the optimal solution. In this paper we would like to address the problem of dynamic services composition in an existing framework by considering two QoS parameters that are communication cost and service cost. For this we suggest an algorithm. Some experimental results are also reported that validate the algorithm. © 2012 Springer-Verlag.},
author_keywords = {communication cost; Dynamic web services composition; quality of services; service cost},
keywords = {Communication cost; Dynamic services composition; Multi-objective optimization problem; Optimal solutions; Optimization algorithms; QoS parameters; Service compositions; Service costs; Service overlay networks; Web services composition, Algorithms; Communication; Overlay networks; Quality of service; Web services; Websites, Costs},
sponsors = {Universidade Federal da Bahia (UFBA); Universidade Federal do Reconcavo da Bahia (UFRB); Universidade Estadual de Feira de Santana (UEFS); University of Perugia; University of Basilicata (UB)},
address = {Salvador de Bahia},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Gentili2012539,
author = {Gentili, E. and Milani, A. and Poggioni, V.},
title = {Data summarization model for user action log files},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2012},
volume = {7335 LNCS},
number = {PART 3},
pages = {539-549},
doi = {10.1007/978-3-642-31137-6_41},
note = {Conference of 12th International Conference on Computational Science and Its Applications, ICCSA 2012 ; Conference Date: 18 June 2012 Through 21 June 2012; Conference Code:90945},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863919526&doi=10.1007%2f978-3-642-31137-6_41&partnerID=40&md5=18c953c7ee10dd67caad673655c92514},
abstract = {During last years we have seen an impressive growth and diffusion of applications shared and used by a huge amount of users around the world, like for example social networks, web portals or elearning platforms. Such systems produce in general a large amount of data, normally stored in its raw format in log file systems and databases. To prevent an unmanageable growing of the necessary space to store data and the breakdown of data usability, such data can be condensed and summarized to improve reporting performance and reduce the system load. This data summarization reduces the amount of space that is required to store software data but produces, as a side effect, a decrease of their informative capability due to an information loss. In this work the problem of summarizing data obtained by the log systems of applications with a lot of users is studied. In particular a model to represent these raw data as temporal events collected in time sequences is proposed, methods to reduce the data size, collapsing the descriptions of more events in a unique descriptor or in a smaller set of descriptors, are provided and the optimal summarization problem is posed. © 2012 Springer-Verlag.},
keywords = {Data size; Data summarizations; Data usability; Descriptors; E-learning platforms; Information loss; Log file; Side effect; Social Networks; Software data; System loads; Time sequences; User action, Artificial intelligence, Data reduction},
sponsors = {Universidade Federal da Bahia (UFBA); Universidade Federal do Reconcavo da Bahia (UFRB); Universidade Estadual de Feira de Santana (UEFS); University of Perugia; University of Basilicata (UB)},
address = {Salvador de Bahia},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Leung2012,
author = {Leung, C.H.C. and Chan, A.W.S. and Milani, A. and Liu, J. and Li, Y.},
title = {Intelligent social media indexing and sharing using an adaptive indexing search engine},
journal = {ACM Transactions on Intelligent Systems and Technology},
year = {2012},
volume = {3},
number = {3},
doi = {10.1145/2168752.2168761},
art_number = {47},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84863632991&doi=10.1145%2f2168752.2168761&partnerID=40&md5=e26d8af3885cbddb1bf2aef2234a6269},
abstract = {Effective sharing of diverse social media is often inhibited by limitations in their search and discovery mechanisms, which are particularly restrictive for media that do not lend themselves to automatic processing or indexing. Here, we present the structure and mechanism of an adaptive search engine which is designed to overcome such limitations. The basic framework of the adaptive search engine is to capture human judgment in the course of normal usage from user queries in order to develop semantic indexes which link search terms to media objects semantics. This approach is particularly effective for the retrieval of multimedia objects, such as images, sounds, and videos, where a direct analysis of the object features does not allow them to be linked to search terms, for example, nontextual/icon-based search, deep semantic search, or when search terms are unknown at the time the media repository is built. An adaptive search architecture is presented to enable the index to evolve with respect to user feedback, while a randomized query-processing technique guarantees avoiding local minima and allows the meaningful indexing of new media objects and new terms. The present adaptive search engine allows for the efficient community creation and updating of social media indexes, which is able to instill and propagate deep knowledge into social media concerning the advanced search and usage of media resources. Experiments with various relevance distribution settings have shown efficient convergence of such indexes, which enable intelligent search and sharing of social media resources that are otherwise hard to discover. © 2012 ACM 2157-6904/2012/05-ART47 $10.00.},
author_keywords = {Adaptive indexing; Evolutionary computation; Genetic algorithms; Multimedia semantics; Relevance feedback; Social media},
keywords = {Adaptive search; Automatic processing; Deep knowledge; Direct analysis; Human judgments; Intelligent search; Local minimums; Media objects; Multimedia object; Multimedia semantics; New media; Relevance feedback; Search terms; Semantic search; Social media; User feedback; User query, Evolutionary algorithms; Feedback; Genetic algorithms; Indexing (of information); Search engines; Semantics, Indexing (materials working)},
document_type = {Article},
source = {Scopus}
}
@article{Milani2012157,
author = {Milani, A. and Santucci, V.},
title = {Community of scientist optimization: An autonomy oriented approach to distributed optimization},
journal = {AI Communications},
year = {2012},
volume = {25},
number = {2},
pages = {157-172},
doi = {10.3233/AIC-2012-0526},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84864438709&doi=10.3233%2fAIC-2012-0526&partnerID=40&md5=b651bb6c5d98afd8c1ccb8e8c71725ea},
abstract = {A novel optimization paradigm, called Community of Scientists Optimization (CoSO), is presented in this paper. The approach is inspired to the behaviour of a community of scientists interacting, pursuing for research results and foraging the funds needed to held their research activities. The CoSO metaphor can be applied to general optimization domains, where optimal solutions emerge from the collective behaviour of a distributed community of interacting autonomous entities. The CoSO framework presents analogies and remarkable differences with other evolutionary optimization approaches: swarm behaviour, foraging and selection mechanism based on research funds competition, dynamically evolving multicapacity communication channels realized by journals and evolving population size regulated by research management strategies. Experiments and comparisons on benchmark problems show the effectiveness of the approach for numerical optimization. CoSO, with the design of appropriate foraging and competition strategies, also represents a great potential as a general meta-heuristic for applications in non-numerical and agent-based domains. © 2012 - IOS Press and the authors. All rights reserved.},
author_keywords = {autonomy oriented optimization; Evolutionary optimization; numerical optimization},
keywords = {Cobalt compounds; Population statistics; Sulfur compounds, Autonomous entities; Collective behaviour; Competition strategy; Distributed optimization; Evolutionary optimizations; General optimizations; Numerical optimizations; Research activities, Optimization},
publisher = {IOS Press},
document_type = {Article},
source = {Scopus}
}
@conference{Santucci2011687,
author = {Santucci, V. and Milani, A.},
title = {Covariance-based parameters adaptation in differential evolution},
journal = {Genetic and Evolutionary Computation Conference, GECCO'11 - Companion Publication},
year = {2011},
pages = {687-690},
doi = {10.1145/2001858.2002069},
note = {Conference of 13th Annual Genetic and Evolutionary Computation Conference, GECCO'11 ; Conference Date: 12 July 2011 Through 16 July 2011; Conference Code:86136},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-80051949865&doi=10.1145%2f2001858.2002069&partnerID=40&md5=a6de2dbd56b2b907ecf1305ac12a1724},
abstract = {Differential Evolution (DE) is a popular and efficient optimization technique for real-valued spaces based on the concepts of Darwinian evolution. Its main peculiarity is the use of a differential mutation operator that allows DE to automatically adjust the exploration/exploitation balance of its search moves. The major DE drawback is the need of a preliminary tuning of some numerical parameters. Although, recently some parameters adaptive schemes have been proposed, none of these takes into account the side effects introduced by changing two or more parameters at the same time. In this paper we introduce a DE self-adaptive scheme that takes into account the parameters dependencies by means of a multivariate probabilistic technique based on an Estimation of Distribution Algorithm working on the parameters space. Experiments have been performed on a set of commonly adopted benchmark problems and the obtained results show the competitiveness of our approach with respect to other adaptive DE schemes. Moreover, our scheme could be potentially adopted not only in DE but also in any other Evolutionary Algorithm or meta-heuristic technique presenting parameters that regulate the behavior of the search. © 2011 ACM.},
author_keywords = {covariance matrix; differential evolution; estimation of distribution algorithms; parameters adaptation},
keywords = {Bench-mark problems; Darwinian evolution; differential evolution; estimation of distribution algorithms; Meta-heuristic techniques; Mutation operators; Numerical parameters; Optimization techniques; parameters adaptation; Parameters adaptive; Probabilistic technique; Self-adaptive; Side effect, Biology; Competition; Covariance matrix; Evolutionary algorithms; Heuristic algorithms; Heuristic methods; Mathematical operators; Parameterization; Probability distributions, Parameter estimation},
sponsors = {Assoc. Comput. Mach., Spec. Interest; Group Genet. Evol. Comput. (ACM SIGEVO)},
address = {Dublin},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Bhardwaj2011537,
author = {Bhardwaj, S. and Niyogi, R. and Milani, A.},
title = {Performance analysis of an algorithm for computation of betweenness centrality},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2011},
volume = {6786 LNCS},
number = {PART 5},
pages = {537-546},
doi = {10.1007/978-3-642-21934-4_44},
note = {Conference of 2011 International Conference on Computational Science and Its Applications, ICCSA 2011 ; Conference Date: 20 June 2011 Through 23 June 2011; Conference Code:85480},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960287101&doi=10.1007%2f978-3-642-21934-4_44&partnerID=40&md5=a2a6a267d5d69ff4f54f3a648508ba49},
abstract = {In social network analysis, graph-theoretic perceptions are used to realize and explain social experience. Centrality indices are essential in the analysis of social networks, but are costly to compute. An efficient algorithm for the computation of betweenness centrality is given by Brandes that has time complexity O(nm + n2logn) and O(n + m) space complexity, where n, m are the number of vertices and edges in a graph, respectively. Some social network graphs are invariably huge and dense. Moreover, size of memory is rapidly increasing and the cost of memory is decreasing day by day. Under these circumstances, we investigate how the computation of centrality measures can be done efficiently when space is not very significant. In this paper, we introduce a time efficient and scalable algorithm for the accurate computation of betweenness centrality. We have made a thorough analysis of our algorithm vis-à-vis Brandes' algorithm. Experimental results show that our algorithm has a better performance with respect to time, but at the expense of using higher memory. Further performance improvement of our algorithm has been achieved by implementing it on parallel architectures. © 2011 Springer-Verlag.},
author_keywords = {betweenness centrality; Social networks},
keywords = {Betweenness centrality; Centrality measures; Efficient algorithm; Graph-theoretic; Performance analysis; Performance improvements; Scalable algorithms; Social Network Analysis; Social networks; Space complexity; Time complexity, Algorithms; Electric network analysis; Graph theory; Parallel architectures; Social networking (online), Computational efficiency},
sponsors = {Univ. Cantabria, Dep. Appl. Math. Comput. Sci.; Univ. Cantabria, Dep. Math., Stat. Comput.; University of Cantabria, Faculty of Sciences; Univ. Cantabria, Vicerrector Res. Knowl. Transf.; The University of Cantabria},
address = {Santander},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2011239,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {Finding P-maps and I-maps to represent conditional independencies},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2011},
volume = {6717 LNAI},
pages = {239-250},
doi = {10.1007/978-3-642-22152-1_21},
note = {Conference of 11th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2011 ; Conference Date: 29 June 2011 Through 1 July 2011; Conference Code:85481},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960146093&doi=10.1007%2f978-3-642-22152-1_21&partnerID=40&md5=05db86fff8985b7650e689ddd328883d},
abstract = {The representation problem of independence models is studied by focusing on acyclic directed graph (DAG). We present the algorithm PC* in order to look for a perfect map. However, when a perfect map does not exist, so that PC* fails, it is interesting to find a minimal I-map, which represents as many triples as possible in J *. Therefore we describe an algorithm which finds such a map by means of a backtracking procedure. © 2011 Springer-Verlag Berlin Heidelberg.},
author_keywords = {DAG; Independence map; Independence models; Perfect map},
keywords = {Acyclic directed graph; DAG; Independence map; Independence models; Perfect map; Acyclic directed graph; Independence models, Algorithms; Directed graphs, Artificial intelligence; Computer science; Computers},
sponsors = {Belfast City Council; Center for Secure Information Technology (CSIT); Queen's Univ. Belfast, Sch. Electron., Electr. Eng. Comput. Sci.},
address = {Belfast},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2011187,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Rossi, F.},
title = {Experimental evaluation of pheromone models in ACOPlan},
journal = {Annals of Mathematics and Artificial Intelligence},
year = {2011},
volume = {62},
number = {3-4},
pages = {187-217},
doi = {10.1007/s10472-011-9265-7},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84856554664&doi=10.1007%2fs10472-011-9265-7&partnerID=40&md5=bd10f561d4e477e092aff83bc7c50a40},
abstract = {In this paper the system ACOPlan for planning with non uniform action cost is introduced and analyzed. ACOPlan is a planner based on the ant colony optimization framework, in which a colony of planning ants searches for near optimal solution plans with respect to an overall plan cost metric. This approach is motivated by the strong similarity between the process used by artificial ants to build solutions and the methods used by state-based planners to search solution plans. Planning ants perform a stochastic and heuristic based search by interacting through a pheromone model. The proposed heuristic and pheromone models are presented and compared through systematic experiments on benchmark planning domains. Experiments are also provided to compare the quality of ACOPlan solution plans with respect to state of the art satisficing planners. The analysis of the results confirm the good performance of the Action-Action pheromone model and points out the promising performance of the novel Fuzzy-Level-Action pheromone model. The analysis also suggests general principles for designing performant pheromone models for planning and further extensions of ACOPlan to other optimization models. © 2011 Springer Science+Business Media B.V.},
author_keywords = {Ant colony optimization; Automated planning},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti2011580,
author = {Baioletti, M. and Coletti, G. and Petturiti, D. and Vantaggi, B.},
title = {Inferential models and relevant algorithms in a possibilistic framework},
journal = {International Journal of Approximate Reasoning},
year = {2011},
volume = {52},
number = {5},
pages = {580-598},
doi = {10.1016/j.ijar.2010.12.006},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79954421933&doi=10.1016%2fj.ijar.2010.12.006&partnerID=40&md5=f15c3f6ce73c5ff8c33c7cb690db85a5},
abstract = {We provide a general inferential procedure based on coherent conditional possibilities and we show, by some examples, its possible use in medical diagnosis. In particular, the role of the likelihood in possibilistic setting is discussed and once the coherence of prior possibility and likelihood is checked, we update prior possibilities. © 2010 Elsevier Inc. All rights reserved.},
author_keywords = {Coherence; Inference; Likelihood; Possibility; Probability},
keywords = {Coherence; Conditional possibility; Inference; Inferential models; Likelihood; Medical diagnosis; Possibilistic; Possibility, Diagnosis, Probability},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2011565,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {Exploiting independencies to compute semigraphoid and graphoid structures},
journal = {International Journal of Approximate Reasoning},
year = {2011},
volume = {52},
number = {5},
pages = {565-579},
doi = {10.1016/j.ijar.2010.11.001},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79954414538&doi=10.1016%2fj.ijar.2010.11.001&partnerID=40&md5=aa66a701c76a405e2def82cba227bbb6},
abstract = {We deal with conditional independencies, which have a fundamental role in probability and multivariate statistics. The structure of probabilistic independencies is described by semigraphoids or, for strictly positive probabilities, by graphoids. In this paper, given a set of independencies compatible with a probability, the attention is focused toward the problem of computing efficiently the closure with respect to the semigraphoid and graphoid structures. We introduce a suitable notion of projection in order to provide a new method which properly uses conditional independence statements. © 2010 Elsevier Inc. All rights reserved.},
author_keywords = {Graphoid; Independence models; Inferential rules; Projection; Semigraphoid},
keywords = {Graphoid; Independence models; Inferential rules; Projection; Semigraphoid, Multivariant analysis, Probability},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Leung201145,
author = {Leung, C. and Li, Y. and Liu, J. and Milani, A.},
title = {Community adaptive educational games},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2011},
volume = {6537 LNCS},
pages = {45-54},
doi = {10.1007/978-3-642-20539-2_6},
note = {Conference of STEG, CICW, WGLBWS, and IWKDEWL, ICWL 2010 Workshops ; Conference Date: 7 December 2010 Through 11 December 2010; Conference Code:84909},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79958017331&doi=10.1007%2f978-3-642-20539-2_6&partnerID=40&md5=f564b4b9ba657288a349b88aef2a4243},
abstract = {This paper presents an adaptive architecture for educational games which are evolved and optimized in order to fulfill the educational goals while reflecting the specific requirements and features of the user community. The approach is based on an online genetic framework where typical genetic operators like crossover and mutation are designed to evolve a population of games, and the online fitness driving the evolution is given by a metric of user behavior/performance, evaluated on the actual community of users. The evolutionary structure adapt can also be applied for continuous game adaptation in dynamical domains where the user community and/or the educational goals are changing over the time. © 2011 Springer-Verlag.},
author_keywords = {community adaptive games; educational game; genetic algorithms},
keywords = {Adaptive architecture; community adaptive games; Crossover and mutation; Educational game; Educational goals; Genetic operators; User behaviors; User communities, Behavioral research; Biology; Genetic algorithms; Mathematical operators; User interfaces, Education},
address = {Shanghai},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti20111,
author = {Baioletti, M. and Petturiti, D.},
title = {Algorithms for possibility assessments: Coherence and extension},
journal = {Fuzzy Sets and Systems},
year = {2011},
volume = {169},
number = {1},
pages = {1-25},
doi = {10.1016/j.fss.2011.01.001},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79951556973&doi=10.1016%2fj.fss.2011.01.001&partnerID=40&md5=d2659fa009363792a3d8ae79fa5dabf2},
abstract = {In this paper we study the computational aspects of coherence and extension of partial possibility assessments, both in an unconditional and a conditional setting, providing complexity results and algorithms for each problem. In particular, we propose an algorithm to check the coherence of a partial unconditional assessment which is based on propositional satisfiability. For the conditional case, we firstly prove a new characterization of coherent conditional assessments that allows us to define an algorithm again based on propositional satisfiability. The extension problem, in both settings, is solved by means of a search algorithm which relies on the corresponding coherence procedure. © 2011 Elsevier B.V. All rights reserved.},
author_keywords = {Algorithms; Coherence; Complexity; Conditioning; Extension; Possibility theory},
keywords = {Coherence; Complexity; Conditioning; Extension; Possibility theory, Formal logic, Algorithms},
document_type = {Article},
source = {Scopus}
}
@article{Santucci201187,
author = {Santucci, V. and Milani, A.},
title = {Particle Swarm Optimization in the EDAs framework},
journal = {Advances in Intelligent and Soft Computing},
year = {2011},
volume = {96 AISC},
pages = {87-96},
doi = {10.1007/978-3-642-20505-7_7},
note = {Conference of 15th Online World Conference on Soft Computing in Industrial Applications, WSC15 ; Conference Date: 15 November 2010 Through 27 November 2010; Conference Code:93527},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867796025&doi=10.1007%2f978-3-642-20505-7_7&partnerID=40&md5=22d7fd2ab759bfe3e578f17ce1f39991},
abstract = {Particle Swarm Optimization (PSO) is a popular optimization technique based on swarm intelligence concepts. Estimation of Distribution Algorithms (EDAs) are a relatively new class of evolutionary algorithms which build a probabilistic model of the population dynamics and use this model to sample new individuals. Recently, the hybridization of PSO and EDAs is emerged as a new research trend. In this paper, we introduce a new hybrid approach that uses a mixture of Gaussian distributions. The obtained algorithm, called PSEDA, can be seen as an implementation of the PSO behaviour in the EDAs framework. Experiments on well known benchmark functions have been held and the performances of PSEDA are compared with those of classical PSO. © Springer-Verlag Berlin Heidelberg 2011.},
keywords = {Gaussian distribution; Soft computing, Benchmark functions; Estimation of distribution algorithms; Hybrid approach; Optimization techniques; Probabilistic modeling; Research trends, Particle swarm optimization (PSO)},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti20112,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {Acyclic directed graphs representing independence models},
journal = {International Journal of Approximate Reasoning},
year = {2011},
volume = {52},
number = {1},
pages = {2-18},
doi = {10.1016/j.ijar.2010.09.005},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78649316701&doi=10.1016%2fj.ijar.2010.09.005&partnerID=40&md5=a10ec0d0c528fe75fe092b4e73a39a48},
abstract = {In this paper we study the problem of representing probabilistic independence models, in particular those closed under graphoid properties. We focus on acyclic directed graph (DAG): a new algorithm to build a DAG, given an ordering among random variables, is described and peculiarities and advantages of this approach are discussed. Moreover, we provide a necessary and sufficient condition for the existence of a perfect map representing an independence model and we describe an algorithm based on this characterization. © 2010 Elsevier Inc. All rights reserved.},
author_keywords = {Acyclic directed graphs; Graphoid properties; Independence models; Inferential rules; Perfect map},
keywords = {Acyclic directed graph; Graphoid properties; Independence models; Inferential rules; Perfect map, Random variables, Graph theory},
document_type = {Conference Paper},
source = {Scopus}
}
@book{Leung2010287,
author = {Leung, C.H.C. and Liu, J. and Milani, A. and Chan, A.W.S.},
title = {Adaptive indexing for semantic music information retrieval},
journal = {Machine Learning Techniques for Adaptive Multimedia Retrieval: Technologies, Applications, and Perspectives},
year = {2010},
pages = {287-300},
doi = {10.4018/978-1-61692-859-9.ch013},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84899361892&doi=10.4018%2f978-1-61692-859-9.ch013&partnerID=40&md5=cd39148b2ab3df6e59276a64986c8d4c},
abstract = {With the rapid advancement of music compression and storage technologies, digital music can be easily created, shared and distributed, not only in computers, but also in numerous portable digital devices. Music often constitutes a key component in many multimedia databases, and as they grow in size and complexity, their meaningful search and retrieval become important and necessary. Music Information Retrieval (MIR) is a relatively young and challenging research area started since the late 1990s. Although some form of music retrieval is available on the Internet, these tend to be inflexible and have significant limitations. Currently, most of these music retrieval systems only rely on low-level music information contents (e.g., metadata, album title, lyrics, etc.), and in this chapter, the authors present an adaptive indexing approach to search and discover music information. Experimental results show that through such an indexing architecture, high-level music semantics may be incorporated into search strategies. © 2011, IGI Global.},
publisher = {IGI Global},
document_type = {Book Chapter},
source = {Scopus}
}
@article{Baioletti20101,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {An Algorithm to Find a Perfect Map for Graphoid Structures},
journal = {Communications in Computer and Information Science},
year = {2010},
volume = {80 PART 1},
pages = {1-10},
doi = {10.1007/978-3-642-14055-6_1},
note = {Conference of Information Processing and Management of Uncertainty in Knowledge-Based Systems: Theory and Methods, 13th International Conference, IPMU 2010, Proceedings ; Conference Date: 28 June 2010 Through 2 July 2010; Conference Code:98055},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79960113850&doi=10.1007%2f978-3-642-14055-6_1&partnerID=40&md5=f32b0626931a7fb6f822e876411df1c3},
abstract = {We provide a necessary and sufficient condition for the existence of a perfect map representing an independence model and we give an algorithm for checking this condition and drawing a perfect map, when it exists. © Springer-Verlag Berlin Heidelberg 2010.},
author_keywords = {Acyclic directed graphs; Conditional independence models; Inferential rules; Perfect map},
keywords = {Acyclic directed graph; Conditional independences; Independence models; Inferential rules; Sufficient conditions, Algorithms; Data processing; Knowledge based systems; Model checking, Information management},
address = {Dortmund},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2010,
author = {Milani, A. and Santucci, V.},
title = {Asynchronous differential evolution},
journal = {2010 IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010},
year = {2010},
doi = {10.1109/CEC.2010.5586107},
art_number = {5586107},
note = {Conference of 2010 6th IEEE World Congress on Computational Intelligence, WCCI 2010 - 2010 IEEE Congress on Evolutionary Computation, CEC 2010 ; Conference Date: 18 July 2010 Through 23 July 2010; Conference Code:85187},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79959410418&doi=10.1109%2fCEC.2010.5586107&partnerID=40&md5=daecfb4ffcd627e1f229442a429782da},
abstract = {This paper introduces the Asynchronous Differential Evolution (ADE) scheme which generalizes the classical Differential Evolution (DE) approach along the dimension of Synchronization Degree (SD). SD regulates the synchrony of the evolution of the current population, i.e. how fast it is replaced by the newly generated population. The definition of the ADE scheme is given and different synchronization strategies are discussed. The introduction of SD parameter allows the tuning of the differential evolution from a completely asynchronous behavior to a super-synchronous behavior. Experiments show that a low SD generally improves the convergence speed and the convergence probability with respect to the classical synchronous DE. Moreover the ordering strategies introduced in ADE seem to improve the performances of the only already known asynchronous variant of DE (the Dynamical Differential Evolution Strategy). © 2010 IEEE.},
keywords = {Asynchronous behavior; Convergence speed; Differential Evolution; Differential evolution strategy; Ordering strategy; Super-synchronous; Synchronization strategies, Artificial intelligence, Evolutionary algorithms},
address = {Barcelona},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2010339,
author = {Milani, A. and Santucci, V. and Leung, C.},
title = {Optimal design of web information contents for e-commerce applications},
journal = {Lecture Notes in Electrical Engineering},
year = {2010},
volume = {62 LNEE},
pages = {339-344},
doi = {10.1007/978-90-481-9794-1_64},
note = {Conference of 25th International Symposium on Computer and Information Sciences, ISCIS 2010 ; Conference Date: 22 September 2010 Through 24 September 2010; Conference Code:82255},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78651574596&doi=10.1007%2f978-90-481-9794-1_64&partnerID=40&md5=70c32a1956280de60a3c849e37ce990a},
abstract = {Optimization of web content presentation poses a key challenge for e-commerce applications. Whether considering web pages, advertising banners or any other content presentation media on the web, the choice of the appropriate structure and appearance with respect to the given audience can obtain a more effective and successful impact on users, such as gathering more readers to web sites or customers to online shops. Here, the collective optimization of web content presentation based on the online discrete Particle Swarm Optimization (PSO) model is presented. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drives particles' velocities in the hybrid continuous-discrete space of web content features. The PSO coordinates the process of sampling collective user behaviour in order to optimize a given user-based metric. Experiments in the online banner optimization scenario show that the method converges faster than other methods and avoid some common drawbacks such as local optima and hybrid discrete/continuous features management. The proposed online optimization method is sufficiently general and may be applied to other web marketing or business intelligence contexts. © 2011 Springer Science+Business Media B.V.},
author_keywords = {collaborative intelligence; collective behaviour mining; Web marketing optimization},
keywords = {Advertising banners; Business intelligence; collaborative intelligence; Collective behaviour; Content presentation; Discrete particle swarm optimization; Discrete spaces; Discrete/continuous; E-Commerce applications; Local optima; Objective functions; Online optimization; Online shops; Optimal design; User behaviour; User feedback; Web content; Web information; Web marketing; Web page, Artificial intelligence; Behavioral research; Electronic commerce; Information science; Marketing; Websites, Particle swarm optimization (PSO)},
address = {London},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Leung2010121,
author = {Leung, C.H.C. and Liu, J. and Milani, A. and Chan, W.S.},
title = {Mining of semantic image content using collective web intelligence},
journal = {Advanced Information and Knowledge Processing},
year = {2010},
volume = {52},
pages = {121-135},
doi = {10.1007/978-1-84996-077-9_6},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84951277570&doi=10.1007%2f978-1-84996-077-9_6&partnerID=40&md5=09a951345874cdc5c0bac2999bd13239},
abstract = {Human users spend a vast amount of time in interacting with image contents on the Web. Their interaction entails the exercise of considerable perceptive intelligence, visual judgment and mental evaluation. For high-level semantic image features and concepts, such processes of intelligent judgment cannot be mechanized or carried out automatically by machines. In this chapter, an indexing method is described whereby the aggregate intelligence of different Web users is continuously transferred to the Web. Such intelligence is codified, reinforced, distilled and shared among users so as to enable the systematic mining and discovery of semantic image contents. This method allows the collaborative creation of image indexes, which is able to instill and propagate deep knowledge and collective wisdom into the Web concerning the advanced semantic characteristics of Web images. This method is robust and adaptive, and is able to respond dynamically to changing usage patterns caused by community trends and social networking. © Springer-Verlag London Limited 2010.},
publisher = {Springer-Verlag London Ltd},
document_type = {Book Chapter},
source = {Scopus}
}
@conference{Baioletti2010,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Rossi, F.},
title = {Experimental evaluation of pheromone models in ACOPlan},
journal = {CEUR Workshop Proceedings},
year = {2010},
volume = {616},
page_count = {14},
note = {Conference of 17th RCRA 2010 Workshop on Experimental Evaluation of Algorithms for Solving Problems with Combinatorial Explosion ; Conference Date: 10 June 2010 Through 11 June 2010; Conference Code:102621},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84893676077&partnerID=40&md5=ac37a2c6150112643d25fc833d82215b},
abstract = {ACOplan is a planner based on the ant colony optimization framework. Using the ACO framework to solve planning optimization problems, one of the main issues to address is the choice of informative and easy to compute pheromone models. In this paper we present and discuss an experimental evaluation of the several pheromone models implemented in ACOPlan. The experiments have been run solving the problems used in the last planning competition. The results suggest that fuzzy pheromone models represents a suitable tradeoff between performance and cost.},
keywords = {Ant colony optimization; Artificial intelligence; Combinatorial mathematics; Optimization, Experimental evaluation; Optimization problems; Pheromone models; Planning competitions, Problem solving},
sponsors = {},
publisher = {CEUR-WS},
address = {Bologna},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Ukey2010160,
author = {Ukey, N. and Niyogi, R. and Singh, K. and Milani, A. and Poggioni, V.},
title = {A Bidirectional Heuristic Search for web service composition with costs},
journal = {International Journal of Web and Grid Services},
year = {2010},
volume = {6},
number = {2},
pages = {160-175},
doi = {10.1504/IJWGS.2010.033790},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77954433229&doi=10.1504%2fIJWGS.2010.033790&partnerID=40&md5=cdb1a330f39f0f2f861ef617ffb2ccbf},
abstract = {This paper presents a model for web service composition based on navigating the web service dependency graph by bidirectional heuristic algorithm. The algorithm is based on a new domain-independent heuristic, while a cost optimisation strategy that balances optimality and convergence performance is also proposed. Experiments on different types of dependency graphs of varying sizes and number of web services show promising results for the service composition model when compared with state-of-the-art search algorithms. The proposed dependency-graph-based composition model can be extended to more general frameworks such as collective systems and virtual environments where a plurality of agents interact composing different actions, services, or resources. Copyright © 2010 Inderscience Enterprises Ltd.},
author_keywords = {Dependency graph; Heuristic search algorithm; Web service composition},
keywords = {Graphic methods; Heuristic algorithms; Learning algorithms; Modular robots; Optimization; Quality of service; Virtual reality; Websites, Collective systems; Convergence performance; Dependency graphs; Domain independents; Heuristic search algorithms; Service composition model; Service dependency; Web service composition, Web services},
publisher = {Inderscience Publishers},
document_type = {Article},
source = {Scopus}
}
@article{Ukey2010309,
author = {Ukey, N. and Niyogi, R. and Milani, A. and Singh, K.},
title = {A bidirectional heuristic search technique for web service composition},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2010},
volume = {6019 LNCS},
number = {PART 4},
pages = {309-320},
doi = {10.1007/978-3-642-12189-0_27},
note = {Conference of 2010 International Conference on Computational Science and Its Applications, ICCSA 2010 ; Conference Date: 23 March 2010 Through 26 March 2010; Conference Code:80261},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77952316708&doi=10.1007%2f978-3-642-12189-0_27&partnerID=40&md5=4eac728961b1c029cb7ad9470963a6f8},
abstract = {Automatic web services composition has recently received considerable attention from researchers in different fields. In this paper we propose a model based on web service dependency graph and a bidirectional heuristic search algorithm to find composite web services. The proposed algorithm is based on a new domain independent heuristic. Experiments on different types of dependency graphs of varying sizes and number of web services show promising results for the service composition model when compared to state-of-the-art search algorithms. The proposed dependency graph based composition model is, however, not limited to traditional web services but it can be extended to more general frameworks of collective systems where a global intelligent behavior emerges by a plurality of agents which interact composing different actions, services, or resources. © 2010 Springer-Verlag Berlin Heidelberg.},
author_keywords = {Dependency graph; Heuristic search algorithm; Web service composition},
keywords = {Graph algorithms; Graphic methods; Heuristic algorithms; Learning algorithms; Quality of service; Websites, Composite Web services; Dependency graphs; Heuristic search algorithms; Heuristic search technique; Intelligent behavior; Service composition model; Web service composition; Web services composition, Web services},
sponsors = {et al.; Kyushu Sangyo University; La Trobe University; Monash University; University of Basilicata; University of Perugia},
publisher = {Springer Verlag},
address = {Fukuoka},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti200911,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {Closure of independencies under graphoid properties: Some experimental results},
journal = {ISIPTA 2009 - Proceedings of the 6th International Symposium on Imprecise Probability: Theories and Applications},
year = {2009},
pages = {11-19},
note = {Conference of 6th International Symposium on Imprecise Probability: Theories and Applications, ISIPTA 2009 ; Conference Date: 14 July 2009 Through 18 July 2009; Conference Code:98795},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880457951&partnerID=40&md5=4a2a3f4a4a8a510023073ad36d4b02fa},
abstract = {In this paper we describe an algorithm for computing the closure with respect to graphoid properties of a set of independencies. Since the computation of the complete closure is infeasible, we provide a procedure, called FC1, which is based on a unique inference rule and on the elimination of redundant independencies. FC1 is able to compute a reduced form of the closure, called fast closure, which is equivalent to the complete closure, but whose size is much smaller. Some experimental tests have been performed with an implementation of the procedure in order to show the computational behavior of the algorithm. We have also compared the computational cost and the size of the fast closure with the corresponding data for the complete closure.},
author_keywords = {Conditional independence models; Graphoid properties; Inferential rules},
keywords = {Computational costs; Conditional independences; Experimental test; Graphoid properties; Inference rules; Inferential rules, Probability, Algorithms},
sponsors = {Elsevier; Engineering and Physical Sciences Research Council (EPSRC); The London Mathematical Society},
address = {Durham},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani200926,
author = {Milani, A. and Santucci, V. and Leung, C.},
title = {Optimizing web content presentation: A online PSO approach},
journal = {Proceedings - 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2009},
year = {2009},
volume = {3},
pages = {26-29},
doi = {10.1109/WI-IAT.2009.222},
art_number = {5285096},
note = {Conference of 2009 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2009 ; Conference Date: 15 September 2009 Through 18 September 2009; Conference Code:88538},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84856913813&doi=10.1109%2fWI-IAT.2009.222&partnerID=40&md5=f2a3ba8e7b2945b68674b49521a8fd6b},
abstract = {In this paper we propose an approach to optimization of web marketing content based on online discrete particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drive particles velocities in the hybrid continuous-discrete space of web content features. The PSO coordinate the process of sampling collective user behavior in order to optimize the web marketing metric. Experiments in the online banner optimization scenario show that the method converges faster than other methods and avoid some common drawbacks such as local optimal and hybrid discrete/continuous features management. The proposed online optimization method is general and can be applied to other web marketing or business intelligent contexts. © 2009 IEEE.},
author_keywords = {Collaborative intelligence; Collective behavior mining; Web marketing optimization},
keywords = {Business intelligent; Collaborative intelligence; Collective behavior; Content-based; Discrete particle swarm optimization; Discrete/continuous; Local optimal; Objective functions; Online optimization; User behaviors; User feedback; Web content; Web marketing, Behavioral research; Intelligent agents; Marketing; Websites, Particle swarm optimization (PSO)},
sponsors = {IEEE Computer Society; Web Intelligence Consortium (WIC); Association for Computing Machinery (ACM); Banca Popolare di Sondrio; Comune di Milano},
address = {Milano},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2009212,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Rossi, F.},
title = {Optimal planning with ACO},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2009},
volume = {5883 LNAI},
pages = {212-221},
doi = {10.1007/978-3-642-10291-2_22},
note = {Conference of 11th International Conference of the Italian Association for Artificial Intelligence: Emergent Perspectives in Artificial Intelligence, AI IA 2009 ; Conference Date: 9 December 2009 Through 12 December 2009; Conference Code:83279},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650700296&doi=10.1007%2f978-3-642-10291-2_22&partnerID=40&md5=08da44b530b3d8e9b91457794c83996c},
abstract = {In this paper a planning framework based on Ant Colony Optimization techniques is presented. Optimal planning is a very hard computational problem which has been coped with different methodologies. Approximate methods do not guarantee either optimality or completeness, but it has been proved that in many applications they are able to find very good, often optimal, solutions. Our proposal is to use an Ant Colony Optimization approach, based both on backward and forward search over the state space, using different pheromone models and heuristic functions in order to solve sequential optimization planning problems. © Springer-Verlag 2009.},
keywords = {Ant-colony optimization; Approximate methods; Hard computational problem; Heuristic functions; Optimal planning; Optimality; Pheromone models; Planning framework; Sequential optimization; State space, Approximation theory; Heuristic algorithms; Optimization, Artificial intelligence},
sponsors = {Italian Association for Artificial Intelligence (AI IA); University of Modena and Reggio Emilia},
address = {Reggio Emilia},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti2009334,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Rossi, F.},
title = {Ant search strategies for planning optimization},
journal = {ICAPS 2009 - Proceedings of the 19th International Conference on Automated Planning and Scheduling},
year = {2009},
pages = {334-337},
note = {Conference of 19th International Conference on Automated Planning and Scheduling, ICAPS 2009 ; Conference Date: 19 September 2009 Through 23 September 2009; Conference Code:83048},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-78650591009&partnerID=40&md5=f2553852627f6d6c7ebf03d98e8ba8db},
abstract = {In this paper a planning framework based on Ant Colony Optimization techniques is presented. It is well known that finding optimal solutions to planning problems is a very hard computational problem. Stochastic methods do not guarantee either optimality or completeness, but it has been proved that in many applications they are able to find very good, often optimal, solutions. We propose several approaches based both on backward and forward search over the state space, using several heuristics and testing different pheromone models in order to solve sequential optimization planning problems. Copyright © 2009, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.},
keywords = {Ant-colony optimization; Hard computational problem; Optimal solutions; Optimality; Pheromone models; Planning framework; Planning problem; Search strategies; Sequential optimization; State space; Stochastic methods, Scheduling, Optimization},
sponsors = {University of Macedonia; Inst. Cognitive Sci. Technol., Natl. Res. Counc. (ISTC-CNR); Inf. Commun. Technol. Dep., Natl. Res. Counc. (ICT-CNR); ISTC-CNR, Planning and Scheduling Team; National Science Foundation (NSF)},
address = {Thessaloniki},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2009583,
author = {Milani, A. and Santucci, V.},
title = {Online PSO for web marketing optimization},
journal = {Proceedings - IEEE International Conference on e-Business Engineering, ICEBE 2009; IEEE Int. Workshops - AiR 2009; SOAIC 2009; SOKMBI 2009; ASOC 2009},
year = {2009},
pages = {583-587},
doi = {10.1109/ICEBE.2009.92},
art_number = {5342051},
note = {Conference of IEEE International Conference on e-Business Engineering, ICEBE 2009; IEEE Int. Workshops - AiR 2009; SOAIC 2009; SOKMBI 2009; ASOC 2009 ; Conference Date: 21 October 2009 Through 23 October 2009; Conference Code:79854},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77950975734&doi=10.1109%2fICEBE.2009.92&partnerID=40&md5=5aad81eadbf415fba0a1bdb55827f010},
abstract = {In this paper we propose an approach to optimization of web marketing content based on an online particle swarm optimization (PSO) model. The idea behind online PSO is to evaluate the collective user feedback as the PSO objective function which drives particles velocities in the hybrid continuous-discrete space of web content features. PSO coordinates the process of sampling collective user behavior in order to optimize the web marketing metric. To improve the performances a variation to the PSO schema is adopted, this variation consists in a restart of the algorithm if the convergence speed is not good. Experiments in the scenario of the home page of an online shop show that the method converges faster and avoid some common drawbacks such as local optimal and hybrid discrete/continuous features management; however is observed that the restart procedure improves the convergence speed of some difficult instances of the problem without affects the other ones. The proposed online optimization method is general and can be applied to other web marketing or business intelligent contexts. © 2009 IEEE.},
author_keywords = {Collaborative intelligence; Collective behavior mining; Online particle swarm optimization; Web marketing optimization},
keywords = {Collaborative intelligence; Collective behavior; Collective behavior mining; Web marketing; Web marketing optimization, Artificial intelligence; Behavioral research; Convergence of numerical methods; Electronic commerce; Marketing; Technical presentations; Websites, Particle swarm optimization (PSO)},
sponsors = {IEEE Computer Society; Technical Committee on Electronic Commerce (TCEC)},
address = {Macau},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni200919,
author = {Franzoni, V. and Gervasi, O.},
title = {Guidelines for web usability and accessibility on the nintendo Wii},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2009},
volume = {5730 LNCS},
pages = {19-40},
doi = {10.1007/978-3-642-10649-1_2},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-76649129842&doi=10.1007%2f978-3-642-10649-1_2&partnerID=40&md5=03dba4cbbe59a8a5006f609eccc2cc3b},
abstract = {The aim of the present study is to propose a set of guidelines for designing Internet web sites usable and accessible with the Nintendo Wii console. After an accurate analysis of usability issues and of the typical Wii Internet users, twelve usability guidelines will be proposed. These guidelines are focused on visibility, understandability, clickability and compatibility. We then restructured a sample web site according to the guidelines. To prove their effectiveness, we performed the usability tests on a sample of forty individuals, selected among the various categories of potential users of the Nintendo Wii console, after having visited the restructured and the original web sites. The analysis of the resulting information confirmed that the restructured web site is more usable than the original and the improvement is more pronounced for weak categories (elderly and individuals with no experience with web browsing). Furthermore the adoption of the guidelines reduces the difficulties experienced by users with different expertise, in visiting a web site with the Wii console. © 2009 Springer-Verlag Berlin Heidelberg.},
keywords = {Accurate analysis; Internet users; Nintendo WII; Potential users; Understandability; Usability tests; Web browsing; Web usability, Internet; Usability engineering, World Wide Web},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Niyogi2009924,
author = {Niyogi, R. and Milani, A.},
title = {Modeling agents' knowledge in collective evolutionary systems},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2009},
volume = {5592 LNCS},
number = {PART 1},
pages = {924-936},
doi = {10.1007/978-3-642-02454-2_72},
note = {Conference of International Conference on Computational Science and Its Applications, ICCSA 2009 ; Conference Date: 29 June 2009 Through 2 July 2009; Conference Code:77779},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70350648965&doi=10.1007%2f978-3-642-02454-2_72&partnerID=40&md5=1ab26aea1e729bed8046fb1ae0b47de6},
abstract = {Collective evolutionary systems have drawn considerable attention in recent times. One reason for this is the advances in the second generation of web development and design. This has led to the emergence of web-based communities and applications such as social-networking sites and blogs. The collective behavior of the system depends heavily on the performance and the reasoning aspects of the agents. Although logics of knowledge has been extensively studied, its application to domains in collective systems has not been illustrated before. In this paper we analyze some significant evolutionary domains characterized by collective and evolutionary aspects, such as partial observability, distribution, sharing, coordination, and mobility. We show how knowledge in these domains can effectively be modeled using ELMA (epistemic logic for mobile agents), which is an extension of an existing epistemic logic with the notion of space and containment, that entails the concepts of group and collaboration. The need and features of appropriate reasoning and planning mechanisms for collective evolutionary environment are also discussed. © 2009 Springer Berlin Heidelberg.},
keywords = {Collective behavior; Collective systems; Epistemic logic; Evolutionary aspects; Evolutionary domain; Evolutionary system; Modeling agents; Partial observability; Second generation; Web development; Web-based communities, Wireless networks, Mobile agents},
sponsors = {University of Perugia; Monash University; University of Calgary; La Trobe University; Soongsil University},
address = {Seoul},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti2009183,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Rossi, F.},
title = {ACOPlan: Planning with ants},
journal = {Proceedings of the 22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22},
year = {2009},
pages = {183-188},
note = {Conference of 22nd International Florida Artificial Intelligence Research Society Conference, FLAIRS-22 ; Conference Date: 19 March 2009 Through 21 March 2009; Conference Code:78172},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70350518877&partnerID=40&md5=2f657db49c11d4d687985b14f3a0d932},
abstract = {In this paper an application of the meta-heuristic Ant Colony Optimization to optimal planning is presented. It is well known that finding out optimal solutions to planning problem is a very hard computational problem. Approximate methods do not guarantee either optimality or completeness, but it has been proved that in many applications they are able to find very good solutions, often close to optimal ones. Since one of the most performing stochastic method for combinatorial optimization is ACO, we have decided to use this technique to design an algorithm which optimizes plan length in prepositional planning. This algorithm has been implemented and some empirical evaluations have been performed. The results obtained are encouraging and show the feasibility of this approach. Copyright © 2009, Assocation for the Advancement of ArtdicaI Intelligence (www.aaai.org). All rights reserved.},
keywords = {Ant-colony optimization; Approximate methods; Empirical evaluations; Hard computational problem; Metaheuristic; Optimal planning; Optimal solutions; Optimality; Planning problem; Stochastic methods, Combinatorial optimization; Heuristic methods, Artificial intelligence},
address = {Sanibel Island, FL},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2009530,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {Acyclic directed graphs to represent conditional independence models},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2009},
volume = {5590 LNAI},
pages = {530-541},
doi = {10.1007/978-3-642-02906-6_46},
note = {Conference of 10th European Conference on Symbolic and Quantitative Approaches to Reasoning with Uncertainty, ECSQARU 2009 ; Conference Date: 1 July 2009 Through 3 July 2009; Conference Code:77051},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-69049118267&doi=10.1007%2f978-3-642-02906-6_46&partnerID=40&md5=9f3bf4330ef19c7c9f123786ac8e77d2},
abstract = {In this paper we consider conditional independence models closed under graphoid properties. We investigate their representation by means of acyclic directed graphs (DAG). A new algorithm to build a DAG, given an ordering among random variables, is described and peculiarities and advantages of this approach are discussed. Finally, some properties ensuring the existence of perfect maps are provided. These conditions can be used to define a procedure able to find a perfect map for some classes of independence models. © 2009 Springer Berlin Heidelberg.},
author_keywords = {Acyclic directed graphs; Conditional independence models; Graphoid properties; Inferential rules; Perfect map},
keywords = {Acyclic directed graphs; Conditional independence models; Graphoid properties; Inferential rules; Perfect map, Random variables, Graph theory},
sponsors = {Institute of Biomedical Engineering (ISIB-CNR); University of Verona, Department of Computer Science; Fondazione Arena di Verona},
address = {Verona},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti200973,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Rossi, F.},
title = {An ACO approach to planning},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2009},
volume = {5482 LNCS},
pages = {73-84},
doi = {10.1007/978-3-642-01009-5_7},
note = {Conference of 9th European Conference on Evolutionary Computation in Combinatorial Optimization, EvoCOP 2009 ; Conference Date: 15 April 2009 Through 17 April 2009; Conference Code:76606},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-67650691551&doi=10.1007%2f978-3-642-01009-5_7&partnerID=40&md5=beedaf675b5df5a540ad1184ff814dd1},
abstract = {In this paper we describe a first attempt to solve planning problems through an Ant Colony Optimization approach. We have implemented an ACO algorithm, called ACOPlan, which is able to optimize the solutions of propositional planning problems, with respect to the plans length. Since planning is a hard computational problem,metaheuristics are suitable to find good solutions in a reasonable computation time. Preliminary experiments are very encouraging, because ACOPlan sometimes finds better solutions than state of art planning systems. Moreover, this algorithm seems to be easily extensible to other planning models. © Springer-Verlag Berlin Heidelberg 2009.},
keywords = {ACO algorithms; Ant-colony optimization; Computation time; Hard computational problem; Meta heuristics; Planning models; Planning problem; Planning systems; Propositional planning, Combinatorial optimization, Problem solving},
address = {Tubingen},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti20091097,
author = {Baioletti, M. and Busanello, G. and Vantaggi, B.},
title = {Conditional independence structure and its closure: Inferential rules and algorithms},
journal = {International Journal of Approximate Reasoning},
year = {2009},
volume = {50},
number = {7},
pages = {1097-1114},
doi = {10.1016/j.ijar.2009.05.002},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-67449128192&doi=10.1016%2fj.ijar.2009.05.002&partnerID=40&md5=ac906659d235b421822fe53dbc76a94a},
abstract = {In this paper, we deal with conditional independence models closed with respect to graphoid properties. Such models come from different uncertainty measures, in particular in a probabilistic setting. We study some inferential rules and describe methods and algorithms to compute efficiently the closure of a set of conditional independence statements. © 2009 Elsevier Inc. All rights reserved.},
author_keywords = {Closure; Conditional independence models; Generalized inclusion; Graphoid properties; Inferential rules},
keywords = {Closure; Conditional independence models; Generalized inclusion; Graphoid properties; Inferential rules},
document_type = {Article},
source = {Scopus}
}
@article{Milani2009432,
author = {Milani, A. and Leung, C. and Chan, A.},
title = {Community Adaptive Search Engines},
journal = {International Journal of Advanced Intelligence Paradigms},
year = {2009},
volume = {1},
number = {4},
pages = {432-443},
doi = {10.1504/IJAIP.2009.026763},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-79957972044&doi=10.1504%2fIJAIP.2009.026763&partnerID=40&md5=41e4fbb26a288ce5917376cac160983d},
abstract = {This paper introduces Community Adaptive Search Engines (CASE) for multimedia object retrieval. CASE systems adapt their behaviour depending on the collective feedback of the users in order to eventually converge to the optimal answer. The community adaptive approach uses continuous user feedbacks on the lists of returned objects in order to filter out irrelevant objects and promote the relevant ones. An original dealer/opponent game model for CASE is proposed and an evolutionary approach to solve the CASE game is also presented. Experimental results shows convergence to the optimal solution with acceptable performance for real domain sizes. Copyright © 2009 Inderscience Enterprises Ltd.},
author_keywords = {Adaptive information retrieval; Collective knowledge; Evolutionary computation; Game theory},
publisher = {Inderscience Publishers},
document_type = {Article},
source = {Scopus}
}
@conference{Milani20081182,
author = {Milani, A. and Jassó, J. and Suriani, S.},
title = {Soft user behavior modeling in virtual environments},
journal = {Proceedings - 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008},
year = {2008},
volume = {2},
pages = {1182-1187},
doi = {10.1109/ICCIT.2008.403},
art_number = {4682408},
note = {Conference of 3rd International Conference on Convergence and Hybrid Information Technology, ICCIT 2008 ; Conference Date: 11 November 2008 Through 13 November 2008; Conference Code:74851},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-57849145125&doi=10.1109%2fICCIT.2008.403&partnerID=40&md5=7e61cd32b89fb9967d219536806d295a},
abstract = {A framework for online user behavior soft modeling is presented in this work. Behavior models of users in dynamic virtual environments has been described in the literature in terms of timed transition automata which can be compiled in a planning domain. The extended notion of soft timed transition automata is proposed in order to recognize a larger class of user histories. The notion of deviation from the user model allows to assess and evaluate in real time the dynamic behavior of users acting in virtual environments, such as e-learning and e-business platforms. The timed automata model allows to describe virtually infinite sequences of user actions subject to temporal constraints, while soft measures allows to assess recognition of behaviors by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed behavior. The proposed model allow the partial recognition of user history also when the observed actions only partially meets the given behavior model constraints. This approach is more realistic for real time user support systems, with respect to standard boolean model recognition, when more than one user model is potentially available the amount of deviation from the models can be used as guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an elearning platforms and plan compilation of the soft timed automaton show the expressivity of the proposed model. © 2008 IEEE.},
author_keywords = {Automated planning; Timed transition automaton; User behavior},
keywords = {Behavioral research; E-learning; Electronic commerce; Information technology; Internet; Multimedia systems; Real time systems; Robots; Translation (languages); Virtual reality, Automated planning; Behavior models; Boolean models; Dynamic behaviors; Dynamic virtual environments; E - learnings; E businesses; Elearning platforms; Infinite sequences; Online users; Planning domains; Real times; Soft modeling; System supports; Temporal constraints; Timed automata models; Timed automatons; Timed transition automaton; User actions; User behavior; User behavior modeling; User models; User supports; Virtual environments, Automata theory},
address = {Busan},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Jassó2008626,
author = {Jassó, J. and Milani, A. and Pallottelli, S.},
title = {Blended e-learning: Survey of on-line student assessment},
journal = {Proceedings - International Workshop on Database and Expert Systems Applications, DEXA},
year = {2008},
pages = {626-630},
doi = {10.1109/DEXA.2008.115},
art_number = {4624788},
note = {Conference of DEXA 2008, 19th International Conference on Database and Expert Systems Applications ; Conference Date: 1 September 2008 Through 5 September 2008; Conference Code:74818},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-57849085757&doi=10.1109%2fDEXA.2008.115&partnerID=40&md5=45002e2dcbe9eb462d5dee0bd8fc2fb9},
abstract = {The e-studium project (https://estudium.unipg.it/) has experimented the introduction of blended e-learning course support in heterogeneous courses of University of Perugia. The assessment process in the e-studium project consists of two main stages: first students apply for an exam through an additional module purposely developed for e-studium, and integrated in the basic platform; then online exam tests are delivered to the candidate which interacts with a quiz management module. In this paper we report and analyze data collected in the twoyear period 2007-2008, and referring to four Computer Science course exams. Data about exam enrollment, test assessment, number of attempts and time needed for test completion have been analyzed. A comparative time-related analysis has been carried out for the four course exams, relationships between teaching and learning activities performed over the platform have been investigated, and used to evaluate the effectiveness of the proposed approach within an academic setting. © 2008 IEEE.},
author_keywords = {Blended e-learning; e-studium; On-line assessment; Web based assessment},
keywords = {Assessment processes; Blended e-learning; Computer science courses; e-studium; On-line assessment; Online exams; Student assessments; Teaching and learnings; Web based assessment, Administrative data processing; Database systems; Decision support systems; E-learning; Education; Expert systems; Internet; Multimedia systems; Problem solving, Teaching},
address = {Turin},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2008444,
author = {Milani, A. and Leung, C. and Chan, A.},
title = {Adaptive search engines as discovery games: An evolutionary approach},
journal = {MoMM2008 - The 6th International Conference on Advances in Mobile Computing and Multimedia},
year = {2008},
pages = {444-449},
doi = {10.1145/1497185.1497280},
note = {Conference of 6th International Conference on Advances in Mobile Computing and Multimedia, MoMM2008 ; Conference Date: 24 November 2008 Through 26 November 2008; Conference Code:77262},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-70349326145&doi=10.1145%2f1497185.1497280&partnerID=40&md5=b6005cbb62f7e26f0471c950ad7549cd},
abstract = {Adaptive search engines (ASE), used in the retrieval of multimedia objects adapt their behavior depending on the user feedback in order to eventually converge to the optimal answer. The adaptive architecture has been shown to improve the performance in case of multimedia objects retrieval, when pre-indexing techniques are costly or can be applied only partially. The continuous user feedbacks onthe lists of returned objects are used to filter out irrelevant objects and promote the relevant ones. This work propose an original dealer/opponent game model for ASE. The system/user interactive process which takes place in ASE can be modeled as a discovery game between a dealer, the user community which holds a secret consisting in the optimal answer to a query, and an opponent, i.e. the system, which tries to discover the secret by submitting tentative solutions on which it receives the user/dealer feedback. It is shown how the complexity of the game can be related to known games. An evolutionary approach to solve the ASE game is also presented. Experimental results shows convergence to the optimal solution with acceptable performance for real domain size. The proposed schema is quite general and can fit other adaptive search architectures which appear in ebusiness and e-commerce applications. Copyright 2008 ACM.},
author_keywords = {Adaptive information retrieval; Collective knowledge; Evolutionary computation; Game theory},
keywords = {Adaptive architecture; Adaptive information retrieval; Adaptive search; Collective knowledge; Domain size; E-Commerce applications; eBusiness; Evolutionary approach; Evolutionary computation; Game models; Indexing techniques; Interactive process; Multimedia object; Optimal solutions; User communities; User feedback, Computation theory; Electronic commerce; Feedback; Information retrieval; Information services; Mobile computing; Multimedia systems; Optimization; Search engines; World Wide Web, Game theory},
address = {Linz},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2008736,
author = {Milani, A. and Jassó, J. and Suriani, S.},
title = {Modeling online user behavior},
journal = {IEEE International Conference on e-Business Engineering, ICEBE'08 - Workshops: AiR'08, EM2I'08, SOAIC'08, SOKM'08, BIMA'08, DKEEE'08},
year = {2008},
pages = {736-741},
doi = {10.1109/ICEBE.2008.113},
art_number = {4690697},
note = {Conference of IEEE International Conference on e-Business Engineering, ICEBE'08 ; Conference Date: 22 October 2008 Through 24 October 2008; Conference Code:74905},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-58149098044&doi=10.1109%2fICEBE.2008.113&partnerID=40&md5=cc7960974f84266ba5b821709ebbdb09},
abstract = {A framework for online user behavior soft modeling is presented in this work. Behavior models of users in dynamic virtual environments has been described in the literature in terms of timed transition automata which can be compiled in a planning domain. The extended notion of soft timed transition automata is proposed in order to recognize a larger class of user histories. The notion of deviation from the user model allows to assess and evaluate in real time the dynamic behavior of users acting in virtual environments, such as e-learning and e-business platforms. The timed automata model allows to describe virtually infinite sequences of user actions subject to temporal constraints, while soft measures allows to assess recognition of behaviors by evaluating the amount of temporal deviation, additional or omitted actions contained in an observed behavior. The proposed model allow the partial recognition of user history also when the observed actions only partially meets the given behavior model constraints. This approach is more realistic for real time user support systems, with respect to standard boolean model recognition, when more than one user model is potentially available the amount of deviation from the models can be used as guide to generate the system support by anticipation, projection and other known techniques. Experiments based on logs from an e-learning platforms and plan compilation of the soft timed automaton shows the expressivity of the proposed model. © 2008 IEEE.},
author_keywords = {Automated planning; Timed transition automaton; User behavior},
keywords = {Behavioral research; E-learning; Electronic commerce; Internet; Multimedia systems; Real time systems; Robots; Translation (languages); Virtual reality, Automated planning; Behavior models; Boolean models; Dynamic behaviors; Dynamic virtual environments; E - learnings; E businesses; Infinite sequences; Online users; Planning domains; Real times; Soft modeling; System supports; Temporal constraints; Timed automata models; Timed automatons; Timed transition automaton; User actions; User behavior; User models; User supports; Virtual environments, Automata theory},
sponsors = {IEEE Comput. Soc., Tech. Committee on Electronic Commerce (TCEC)},
address = {Xi'an},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Leung2008216,
author = {Leung, C.H.C. and Liu, J. and Chan, A.W.S. and Milani, A.},
title = {An architectural paradigm for collaborative semantic indexing of multimedia data objects},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2008},
volume = {5188 LNCS},
pages = {216-226},
doi = {10.1007/978-3-540-85891-1_24},
note = {Conference of 10th International Conference on Visual Information Systems, VISUAL 2008 ; Conference Date: 11 September 2008 Through 12 September 2008; Conference Code:74230},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-55249125215&doi=10.1007%2f978-3-540-85891-1_24&partnerID=40&md5=b91b08120b9e31b16bd92b4228957fbb},
abstract = {A challenging problem facing the semantic search of multimedia data objects is the ability to index them. Here, we present an architectural paradigm for collaborative semantic indexing, which makes use of a dynamic evolutionary approach. By capturing, analyzing and interpreting user response and query behavior, the patterns of searching and finding multimedia data objects may be established. Within the present architectural paradigm, the semantic index may be dynamically constructed, validated, and built-up, where the performance of the system will increase as time progresses. Our system also incorporates a high degree of robustness and fault-tolerance whereby inappropriate index terms will be gradually eliminated from the index, while appropriate ones will be reinforced. We also incorporate genetic variations into the design to allow objects which may otherwise be hidden to be discovered. Experimental results indicate that the present approach is able to confer significant performance benefits in the semantic searching and discovery of a wide variety of multimedia data objects. © 2008 Springer-Verlag Berlin Heidelberg.},
author_keywords = {Collaborative indexing; Concept-based search; Genetic algorithms; Index set; Multimedia data objects; Ranking; Relevance feedback; Semantics retrieval},
keywords = {Control theory; Diesel engines; Distributed computer systems; Fault tolerance; Feedback; Genetic algorithms; Image retrieval; Indexing (of information); Information systems; Information theory; Ketones; Quality assurance; Reliability; Visual communication, Collaborative indexing; Concept-based search; Index set; Multimedia data objects; Ranking; Relevance feedback, Semantics},
sponsors = {University of Salerno; UniCredit Banca di Roma; Dipartimento di Matematica e Informatica; Unlimited Software srl; Engineering SpA; Pixsta ltd},
address = {Salerno},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti20081000,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Suriani, S.},
title = {Parallel actions and generalized multivalued constraints in multivalued planning},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2008},
volume = {5073 LNCS},
number = {PART 2},
pages = {1000-1011},
doi = {10.1007/978-3-540-69848-7_79},
note = {Conference of International Conference on Computational Science and Its Applications, ICCSA 2008 ; Conference Date: 30 June 2008 Through 3 July 2008; Conference Code:73953},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-54249151576&doi=10.1007%2f978-3-540-69848-7_79&partnerID=40&md5=f7c6c82b80aa3d0257dc4d75927289e3},
abstract = {In this work an extension of the model for planning with multivalued fluents and graded actions introduced in [8] is proposed. This model is based on the infinity-valued Lukasiewicz logic, where the fluents can assume truth values in the interval [0,1] and actions can be executed at different application degrees also varying in [0,1]. Multivalued fluents and graded actions allow to model many real situations where some features of the world are fuzzy and where actions can be executed with varying strength. The main contributions of this paper are given by the introduction of the simultaneous executability of the graded actions and the extension of multivalued constraints to generalized multivalued constraints. An extension of the correct/complete algorithm which solves bounded multivalued planning problems is presented. It allows to solve problems with generalized constraints and simultaneous actions. © 2008 Springer-Verlag Berlin Heidelberg.},
keywords = {Applications, Fluents; Generalized constraints; Lukasiewicz logics; Planning problems; Real situations; Truth values, Computational fluid dynamics},
sponsors = {University of Perugia; University of Calgary; Innovative Computational Science Applications (ICSA); MASTER-UP; University of Calgary, SPARCS Laboratory; OptimaNumerics},
address = {Perugia},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Franzoni2008105,
author = {Franzoni, V. and Gervasi, O. and Tasso, S. and Pallottelli, S.},
title = {Web usability on the Nintendo Wii platform},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2008},
volume = {5073 LNCS},
number = {PART 2},
pages = {105-118},
doi = {10.1007/978-3-540-69848-7_10},
note = {Conference of International Conference on Computational Science and Its Applications, ICCSA 2008 ; Conference Date: 30 June 2008 Through 3 July 2008; Conference Code:73953},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-54249149145&doi=10.1007%2f978-3-540-69848-7_10&partnerID=40&md5=d0a08a4bacef26d3042381328c8f72d0},
abstract = {The aim of the present study is to propose a set of guidelines for designing Internet web sites usable and accessible with the Nintendo Wii console. After an accurate analysis of usability issues and the definition of the typical Wii Internet user, twelve usability guidelines will be described. The named guidelines are focused on the visibility, understandability, clickability and compatibility issues. To prove the effectiveness of the guidelines we have applied them to a test web site. We carried out a comparison test on a sample of forty individuals, selected among the various categories of the potential users of the Nintendo Wii console. The analysis of the resulting information confirms that the revised web site according to our guidelines is more usable and the improvement is more pronounced for weak categories (elderly and individuals with no experience with web browsing). Furthermore the adoption of the guidelines reduces the gap between users with different expertise, accessing a web site with the console. © 2008 Springer-Verlag Berlin Heidelberg.},
keywords = {World Wide Web, Accurate analysis; Comparison tests; Compatibility issues; Internet users; Nintendo WII; Potential users; Understandability; Usability guidelines; Web browsing; Web sites; Web usabilities; Web-site, Internet},
sponsors = {University of Perugia; University of Calgary; Innovative Computational Science Applications (ICSA); MASTER-UP; University of Calgary, SPARCS Laboratory; OptimaNumerics},
address = {Perugia},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Gerace2008497,
author = {Gerace, I. and Mastroleo, M. and Milani, A. and Moraglia, S.},
title = {Genetic blind image restoration with dynamical local evaluation},
journal = {Proceedings - The International Conference on Computational Sciences and its Applications, ICCSA 2008},
year = {2008},
pages = {497-506},
doi = {10.1109/ICCSA.2008.66},
art_number = {4561255},
note = {Conference of International Conference on Computational Sciences and its Applications, ICCSA 2008 ; Conference Date: 30 June 2008 Through 3 July 2008; Conference Code:73459},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-52249106043&doi=10.1109%2fICCSA.2008.66&partnerID=40&md5=20f1a890cb57be9e1643c6fc651db9dd},
abstract = {The blind image restoration problem consists in estimating the original image from blurry and noisy data, without knowing the involved blur operator. The problem is well known to be ill-posed even in the not-blind formulation, nevertheless the use of regularization techniques allows to define the solution of the problem as the minimum of an energy function. In this paper we solve the blind restoration problem with a evolutionary approach. A population of blur operators is evolved with a fitness given by the opposite of the. energy function to be minimized. Since the fitness evaluation, calculated on the whole image, represents a significant computational overhead which can make the method unfeasible for large images, an original technique of dynamical local fitness evaluation has been designed and integrated in the evolutionary scheme. The subimage evaluation area is dynamically changed during evolution of the population. The underlying hypothesis is that the explored subareas are significatively representative of the features of blurs and noises in the global image. The experimental results confirm the adequacy of such a method: in some, cases the proposed genetic blind reconstruction finds qualitatively better solutions outperforming the not-blind standard deterministic algorithm. © 2008 IEEE.},
keywords = {Image reconstruction; Population statistics; Restoration; Solutions; Standards, Blind image restoration; Computational overheads; Computational sciences; Energy functions; Evolutionary approaches; Fitness evaluation; Ill-posed; International conferences; Large images; Noisy data; Original images; Regularization techniques, Repair},
address = {Perugia},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Dascalu2008,
author = {Dascalu, S. and Wang, A.I. and Dragan, I.C. and Ge, S.S. and Nakashima, T. and Milani, A. and Lovell, B.C. and Viniotis, Y. and Latombe, J.-C. and Nearchou, A.C. and Oinas-Kukkonen, H. and Zaytoon, J.},
title = {Proceedings of the 1st International Conference on Advances in Computer-Human Interaction, ACHI 2008: Preface},
journal = {Proceedings of the 1st International Conference on Advances in Computer-Human Interaction, ACHI 2008},
year = {2008},
pages = {x-xi},
doi = {10.1109/ACHI.2008.4},
art_number = {4455948},
note = {Conference of 1st International Conference on Advances in Computer-Human Interaction, ACHI 2008 ; Conference Date: 10 February 2008 Through 15 February 2008; Conference Code:72631},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47349104128&doi=10.1109%2fACHI.2008.4&partnerID=40&md5=16fb5df6fc46f2d340652965ecc983d1},
address = {Saint Luce},
document_type = {Editorial},
source = {Scopus}
}
@article{Milani2008626,
author = {Milani, A. and Leung, C.H.C. and Baioletti, M. and Suriani, S.},
title = {An evolutionary algorithm for adaptive online services in dynamic environment},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2008},
volume = {4974 LNCS},
pages = {626-632},
doi = {10.1007/978-3-540-78761-7_68},
note = {Conference of European Workshops on the Theory and Applications of Evolutionary Computation, EvoWorkshops 2008: EvoCOMNET, EvoFIN, EvoHOT, EvoIASP, EvoMUSART, EvoNUM, EvoSTOC, and EvoTransLog ; Conference Date: 26 March 2008 Through 28 March 2008; Conference Code:72585},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47249124914&doi=10.1007%2f978-3-540-78761-7_68&partnerID=40&md5=5404029e324f788af312eed3b267ff09},
abstract = {An evolutionary adaptive algorithm for solving a class of online service provider problems in a dynamical web environment is introduced. In the online service provider scenario, a system continuously generates digital products and service instances by assembling components (e.g. headlines of online newspapers, search engine query results, advertising lists) to fulfill the requirements of a market of anonymous customers. The evaluation of a service instance can only be known by the feedback obtained after delivering it to the customer over the internet or through telephone networks. In dynamic domains available components and customer/agents preferences are changing over the time. The proposed algorithm employs typical genetic operators in order to optimize the service delivered and to adapt it to the environment feedback and evolution. Differently from classical genetic algorithms the goal of such systems is to maximize the average fitness instead of determining the single best optimal service/product. Experimental results for different classes of services, online newspapers and search engines, confirm the adaptive behavior of the proposed technique. © 2008 Springer-Verlag Berlin Heidelberg.},
keywords = {Adaptive algorithms; Boolean functions; Computation theory; Computer software; Decision theory; Genetic algorithms; Information retrieval; Information services; Internet; Newsprint; Search engines; Telephone; Telephone circuits; Telephone systems; World Wide Web, Adaptive behavior; Classes of services (CoS); Digital products; Dynamic domains; Dynamic environments; European; Evolution (CO); Evolutionary computation (EC); Evolutionary computing; Genetic operators; Heidelberg (CO); On-line services; Online newspapers; Query results; Service instances; Telephone networks; Web environment, Evolutionary algorithms},
sponsors = {Research Center in Pure and Applied Mathematics; Inst. High Performance Computing and Networking, Natl. Res.Counc.; University of Naples Federico II; The Centre for Emergent Computing, Napier University, Edinburgh},
address = {Naples},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Falcinelli2007658,
author = {Falcinelli, E. and Gori, C. and Jasso, J. and Milani, A. and Pallottelli, S.},
title = {E-studium: An Italian experience of blended e-learning for university education support},
journal = {Proceedings - International Workshop on Database and Expert Systems Applications, DEXA},
year = {2007},
pages = {658-662},
doi = {10.1109/DEXA.2007.11},
art_number = {4312976},
note = {Conference of DEXA 2007 18th International Workshop on Database and Expert Systems Applications ; Conference Date: 3 September 2007 Through 7 September 2007; Conference Code:72748},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47849105721&doi=10.1109%2fDEXA.2007.11&partnerID=40&md5=3c942415b345b243d145bf9870089367},
abstract = {In the radically changing framework of education and training, the E-studium project (http://e-studium.unipg.it) developed at the University of Perugia, proposes a dynamic and versatile education system, managing effectively the learning process and using new ICT technologies to respond individually to the needs of a wide audience of students disseminated in the country. The organization model is an integrated e-learning system, known as blended e-learning (realized through the course management system Moodle), aiming at a renewal of academic education with a focus on quality of teaching, on support of in-class teaching by on-line services and materials, allowing better use and participation by both full-time and part-time students. Beside students, also academic teachers work as experimental subjects for the technologies implemented. In this work the "E-studium" project is presented showing the different phases of development, implementation and analysis of results including usage. © 2007 IEEE.},
keywords = {Administrative data processing; Artificial intelligence; Database systems; Decision support systems; E-learning; Education; Education computing; Expert systems; Internet; Learning systems; Management information systems; Multimedia systems; Students; Technology, Course management system; Education and training; Education systems; Integrated e-learning; Learning processes; On-line services; Organization modeling; Quality of teaching; University education, Teaching},
address = {Regensburg},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Falcinelli2007663,
author = {Falcinelli, E. and Falcinelli, F. and Laici, C. and Milani, A.},
title = {Experience of blended e-learning in post-graduate training for High School Teaching Qualification},
journal = {Proceedings - International Workshop on Database and Expert Systems Applications, DEXA},
year = {2007},
pages = {663-667},
doi = {10.1109/DEXA.2007.93},
art_number = {4312977},
note = {Conference of DEXA 2007 18th International Workshop on Database and Expert Systems Applications ; Conference Date: 3 September 2007 Through 7 September 2007; Conference Code:72748},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47849091742&doi=10.1109%2fDEXA.2007.93&partnerID=40&md5=6fb363cecc065cd800a86c13da430b8c},
abstract = {The traditional methods and strategies for educational-learning training in universities do not respond to the learning needs of students applying to "Special Training Courses" (Corsi Abilitanti speciali) that are already experienced teachers and workers, and that for various reasons and motivations are not able to attend classroom courses. In this environment, SSIS Umbria (Post-graduate training for high school teaching qualification) is experimenting a form of blended e-learning aimed at supporting classroom lessons, during which a network approach to knowledge and some forms of collaboration and cooperation in know-how building are integrated. Experimentation has proposed integration of on-line activities that students are able to carry out on their own, and other activities to be performed in small learning groups, consistent with the class courses envisaged for teacher training. The experimentation has also allowed to assess, through log analysis, the degree of interest of participants and distribution of their time between the various activities envisaged by the e-learning software. The method for evaluation of participant activities has not been based on a simple recording of the on-line connection time, but rather on the assignation of a previously-set time "token" in minutes to each task performed, according to the commitment forecast for the accomplishment of each single activity. This type of monitoring has been organized by backing up software time-counting of "minute-amounts" coming from on-line practice with tutor control, in order to supervise the respect of an accurate netiquette. © 2007 IEEE.},
keywords = {Backing-up; Degree of Interest; High schools; Know-how; Learning groups; Log analysis; Netiquette; Set time; Teacher training; Training courses, Administrative data processing; Artificial intelligence; Concurrency control; Database systems; Decision support systems; E-learning; Education; Expert systems; Internet; Management information systems; Multimedia systems; School buildings; Students; Technology transfer, Teaching},
address = {Regensburg},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Jassó2007939,
author = {Jassó, J. and Milani, A.},
title = {User session models for educational systems based on multiple knowledge structures},
journal = {Proceedings - The 7th IEEE International Conference on Advanced Learning Technologies, ICALT 2007},
year = {2007},
pages = {939-940},
doi = {10.1109/ICALT.2007.272},
art_number = {4281209},
note = {Conference of 7th IEEE International Conference on Advanced Learning Technologies, ICALT 2007 ; Conference Date: 18 July 2007 Through 20 July 2007; Conference Code:72702},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-47649107138&doi=10.1109%2fICALT.2007.272&partnerID=40&md5=683d725d213d24d8ae33096b502a9b50},
abstract = {This work introduces a framework for a general representation of web-pages by means of Multiple Knowledge Structures in order to improve semantic usage modelling by multiple semantic information. The proposed approach generalizes existing models, developed mainly for e-commerce systems, in order to include and integrate features of hypertext-structured educational systems such as e-learning systems. © 2007 IEEE.},
keywords = {E-commerce systems; E-Learning systems; Educational systems; International conferences; Knowledge structuring; Learning technologies; Semantic information, E-learning; Electronic commerce; Hypertext systems; Information theory; Internet; Knowledge representation; Learning systems; Multimedia systems; Semantics; Technology, Education},
sponsors = {IEEE Technical Committee on Learning Technology; IEEE Computer Society},
address = {Niigata},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Baioletti2007480,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Suriani, S.},
title = {Interactive dynamic production by genetic algorithms},
journal = {Proceedings of the IASTED International Conference on Artificial Intelligence and Applications, AIA 2007},
year = {2007},
pages = {480-485},
note = {Conference of IASTED International Conference on Artificial Intelligence and Applications, AIA 2007 ; Conference Date: 12 February 2007 Through 14 February 2007; Conference Code:70935},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-38349186395&partnerID=40&md5=b479a6b0de9ae35bb186413b24fa88ea},
abstract = {In this work we introduce an adaptive genetic algorithm for solving a class of interactive production problems in a dynamical environment. In the interactive production problem, a system continuously generates product instances which should meet the requirements of a market of customers/agents which are unknown to it. The only way for the system to know the evaluation of a product instance is the feedback obtained after delivering it to the customer. In a dynamical environment the domain of the products is changing and the customer/agents are changing their preferences over the time. This scenario is common to many IT services and products which are continuously delivered to a mass of anonymous users. The proposed algorithm employs typical genetic operators in order to optimize the product delivered and to adapt it to the environment feedback and evolution. Differently from classical GA the goal of such system is to maximize the average result instead of determining the best optimal solution. Experimental results are promising and show interesting properties of the adaptive behavior of GA techniques.},
author_keywords = {Adaptative systems; Genetic algorithms; Interactive production problem},
keywords = {Adaptive systems; Interactive computer graphics; Mathematical operators; Problem solving; User interfaces, Anonymous users; Interactive production problems; Optimal solution, Genetic algorithms},
sponsors = {The IASTED, Tech. Comm. on Artif. Intelligence and Expert Systems; World Modelling and Simulation Forum (WMSF)},
address = {Innsbruck},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2007439,
author = {Milani, A. and Poggioni, V.},
title = {Planning in reactive environments},
journal = {Computational Intelligence},
year = {2007},
volume = {23},
number = {4},
pages = {439-463},
doi = {10.1111/j.1467-8640.2007.00315.x},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-37249003940&doi=10.1111%2fj.1467-8640.2007.00315.x&partnerID=40&md5=0d573adbab0766bda04f54154eb982d3},
abstract = {The diffusion of domotic and ambient intelligence systems have introduced a new vision in which autonomous deliberative agents operate in environments where reactive responses of devices can be cooperatively exploited to fulfill the agent's goals. In this article a model for automated planning in reactive environments, based on numerical planning, is introduced. A planner system, based on mixed integer linear programming techniques, which implements the model, is also presented. The planner is able to reason about the dynamic features of the environment and to produce solution plans, which take into account reactive devices and their causal relations with agent's goals by exploitation and avoidance techniques, to reach a given goal state. The introduction of reactive domains in planning poses some issues concerning reasoning patterns which are briefly depicted. Experiments of planning in reactive domains are also discussed. © 2007 Blackwell Publishing, Inc.},
author_keywords = {ambient intelligence; automated reasoning; planning; reactive environment},
keywords = {Dynamic models; Linear programming; Pattern recognition; Planning, Ambient intelligence; Automated reasoning; Avoidance techniques; Reactive environment, Multi agent systems},
document_type = {Article},
source = {Scopus}
}
@article{Marcugini2007739,
author = {Marcugini, S. and Milani, A. and Pambianco, F.},
title = {Complete arcs in PG (2, 25): The spectrum of the sizes and the classification of the smallest complete arcs},
journal = {Discrete Mathematics},
year = {2007},
volume = {307},
number = {6},
pages = {739-747},
doi = {10.1016/j.disc.2005.11.094},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33846047585&doi=10.1016%2fj.disc.2005.11.094&partnerID=40&md5=6f82f48040bfe3fe5cf669d07c71f31f},
abstract = {In this paper it has been verified, by an exhaustive computer search, that in PG (2, 25) the smallest size of a complete arc is 12 and that complete 19-arcs and 20-arcs do not exist. Therefore, the spectrum of the sizes of the complete arcs in PG (2, 25) is completely determined. The classification of the smallest complete arcs is also given: the number of non-equivalent complete 12-arcs is 606 and for each of them the automorphism group has been found and some geometrical properties have been studied. The exhaustive search has been feasible because projective equivalence properties have been exploited to prune the search tree and to avoid generating too many isomorphic copies of the same arc. © 2006 Elsevier B.V. All rights reserved.},
author_keywords = {Arcs; Complete arcs; Projective planes},
keywords = {Numerical methods; Spectrum analysis, Automorphism; Complete arcs; Computer search; Projective planes, Computational geometry},
document_type = {Article},
source = {Scopus}
}
@article{Gerace2007242,
author = {Gerace, I. and Mastroleo, M. and Milani, A. and Moraglia, S.},
title = {An evolutionary approach to inverse gray level quantization},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2007},
volume = {4781 LNCS},
pages = {242-253},
doi = {10.1007/978-3-540-76414-4_25},
note = {Conference of 9th International Conference on Visual Information Systems, VISUAL 2007 ; Conference Date: 28 June 2007 Through 29 June 2007; Conference Code:71222},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-38349057925&doi=10.1007%2f978-3-540-76414-4_25&partnerID=40&md5=152c5a5292807016ef612d0b40a23971},
abstract = {The gray levels quantization technique is used to generate images which limit the number of color levels resulting in a reduction of the image size, while it preserves the quality perceived by human observers. The problem is very relevant for image storage and web distribution, as well as in the case of devices with limited bandwidth, storage and/or computational capabilities. An efficient evolutionary algorithm for the inverse gray level quantization problem, based on a technique of dynamical local fitness evaluation, is presented. A population of blur operators is evolved with a fitness given by the energy function to be minimized. In order to avoid the unfeasible computational overhead due to the fitness evaluation calculated on the entire image, an innovative technique of dynamical local fitness evaluation has been designed and integrated in the evolutionary scheme, The sub-image evaluation area is dynamically changed during evolution of the population, and the evolutionary scheme operates a form of machine learning while exploring subárea which are significatively representative of the global image. The experimental results confirm the adequacy of such a method. © Springer-Verlag Berlin Heidelberg 2007.},
author_keywords = {Evolutionary algorithms; Image compression; Machine learning},
keywords = {Bandwidth; Computational complexity; Image compression; Learning systems; Problem solving, Gray level quantization; Image size, Evolutionary algorithms},
publisher = {Springer Verlag},
address = {Shanghai},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2006575,
author = {Baioletti, M. and Milani, A. and Poggioni, V. and Suriani, S.},
title = {A Multivalued logic model of planning},
journal = {Frontiers in Artificial Intelligence and Applications},
year = {2006},
volume = {141},
pages = {575-579},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84886019657&partnerID=40&md5=2ea3ee80d6ae5021bc2a7ebe0525cee7},
abstract = {In this work a model for planning with multivalued fluents and graded actions, based on the infinite valued Lukasiewicz logic, is introduced. In multivalued planning, fluents can assume truth values in the interval [0, 1] and actions can be executed at different application degrees also varying in [0, 1]. The notions of planning problem and solution plan also reflect a multivalued approach. Multivalued fluents and graded actions allow to model many real situations where some features of the world cannot be modeled with boolean values and where actions can be executed with varying strength which produces graded effects as well. Even if most existing planning models fail to address this kind of domains, our model is comparable with models allowing flexible actions and soft constraints. A correct/complete algorithm which solves bounded multivalued planning problems based on MIP compilation is also described and a prototype implementation is presented. © 2006 The authors.},
document_type = {Article},
source = {Scopus}
}
@book{Baioletti200673,
author = {Baioletti, M. and Capotorti, A. and Tulipani, S.},
title = {An empirical complexity study for a 2CPA solver},
journal = {Modern Information Processing},
year = {2006},
pages = {73-84},
doi = {10.1016/B978-044452075-3/50007-8},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84882914872&doi=10.1016%2fB978-044452075-3%2f50007-8&partnerID=40&md5=43a3d1b53b8fa64405bd652b1ac1adea},
abstract = {The computational decision problem, coherent probability assessment (CPA), is a variant of the probabilitistic satisfiability problem PSAT. This chapter investigates the behavior of an algorithm, which decides CPA applied to the still NP-complete subproblem 2CPA. It discusses three generators of random instances for the 2CPA problems. The first two generators share as a first common step the random generation of the probabilities pi, associated to each event Xi, with a uniform distribution in [0,1]. The second step is the random generation of the clauses. A first common principle used in both generators is that clauses must be zero-satisfiable-there must exist a truth assignment on the variables that falsifies all the clauses. It is easy to show that a 2CPA instance, whose clauses are not zero-satisfiable, is incoherent. The problem of checking if a 2CPA has zero-satisfiable clauses is equivalent to 2SAT, and then it is solvable in a time linear with respect to the number of clauses. A second principle is to avoid to generating instances whose clauses violate in an apparent way some rules of probability theory. © 2006 Copyright © 2006 Elsevier B.V. All rights reserved..},
publisher = {Elsevier},
document_type = {Book Chapter},
source = {Scopus}
}
@conference{Falcinelli2006200,
author = {Falcinelli, E. and Marcugini, S. and Milani, A.},
title = {An architecture for dynamical news providers},
journal = {Proceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2006 Workshops Proceedings)},
year = {2006},
pages = {200-203},
doi = {10.1109/WI-IATW.2006.35},
art_number = {4053235},
note = {Conference of 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology ; Conference Date: 18 December 2006 Through 22 December 2006; Conference Code:69803},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250764753&doi=10.1109%2fWI-IATW.2006.35&partnerID=40&md5=cec2466a10155039da84e2ae25dc0098},
abstract = {In this work we introduce an adaptive architecture for supporting news information services in a dynamical web environment. In the news provider problem, a system continuously generates service instances (e.g.the news of a online newspaper) which should meet the requirements of a market of readers/agents which are supposed unknown. The only way for the system to know the evaluation of a service instance, i.e. a newspaper instance, is the feedback obtained after delivering it to the reader. In a dynamical environment the domain of the service offered is changing and the readers/agents are changing their preferences over the time. The proposed algorithm for newpapers production employs typical genetic operators in order to optimize the product delivered and to adapt it to the environment feedback and domain evolution. Experiments shows the capability of dynamical adaptation of the algorithm.. © 2006 IEEE.},
keywords = {Adaptive systems; Computer architecture; Genetic algorithms; Information analysis; Optimization; Problem solving, Adaptive architecture; Online newspaper, Information services},
sponsors = {Association for Computing Machinery (ACM); IEEE Computer Society; Web Intelligence Consortium (WIC)},
publisher = {IEEE Computer Society},
address = {Hong Kong},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2006125,
author = {Milani, A. and Rossi, F. and Pallottelli, S.},
title = {Planning based integration of web services},
journal = {Proceedings - 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2006 Workshops Proceedings)},
year = {2006},
pages = {125-128},
doi = {10.1109/WI-IATW.2006.104},
art_number = {4053218},
note = {Conference of 2006 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology ; Conference Date: 18 December 2006 Through 22 December 2006; Conference Code:69803},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-34250757049&doi=10.1109%2fWI-IATW.2006.104&partnerID=40&md5=4545c93a0f9b4155a26937bb06c3c758},
abstract = {In this paper a planning system for goal directed integration of web services is presented. The presented model extends classical planning to manage some forms of non determinism in service execution and to manage collections of objects. The dynamical evolving domain of available web services require flexible tools for composing the given resources in order to fulfil user goals which are also unpredictable. Automated planning techniques can be efficiently used to realise dynamical and adaptive web service composition. The domain of available services is represented by a set of planning operators, the behaviour of the composed service is described by a final goal and the generated solution plans are used for synthesis of web service scripts. © 2006 IEEE.},
keywords = {Adaptive systems; Decision support systems; Problem solving, Adaptive web service composition; Classical planning, Web services},
sponsors = {Association for Computing Machinery (ACM); IEEE Computer Society; Web Intelligence Consortium (WIC)},
publisher = {IEEE Computer Society},
address = {Hong Kong},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2005748,
author = {Milani, A. and Suriani, S. and Poggioni, V.},
title = {Modeling educational domains in a planning framework},
journal = {ACM International Conference Proceeding Series},
year = {2005},
volume = {113},
pages = {748-753},
doi = {10.1145/1089551.1089687},
note = {Conference of 7th International Conference on Electronic Commerce, ICEC05 ; Conference Date: 15 August 2005 Through 17 August 2005; Conference Code:80710},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77953868458&doi=10.1145%2f1089551.1089687&partnerID=40&md5=90bdf695790f6b882e7fda3a4059cb9a},
abstract = {This paper shows how current planning technology can be used in order to model online educational activity. In particular the automated planning approach allows to model the interactive process of designing the structure of educational tools and entities, such as courses, curricula studiorum, examples and training exercises, handbooks. Planning models allow to exploit educational knowledge bases in order to produce flexible and adaptive tools which are suited on the individual educational needs of the users. In addition to the generation of educational support material, state-of-the-art planning systems can also be used to monitor the interactive learning task of the user. Recent advancements on planning models based on resources management allow to refine and tune user modelling goals in order to realize a personalized service. An example of educational domain model based on planning with resources, is shown, in order to support the dynamical generation and monitoring of web based online courses. Copyright 2005 ACM.},
author_keywords = {adaptive systems; e-learning assessment and planning; knowledge based systems; planning},
keywords = {Automated planning; Domain model; e-learning assessment and planning; Educational activities; Educational knowledge; Educational needs; Educational tools; Interactive learning; Interactive process; Online course; Personalized service; Planning framework; Planning models; Planning systems; Resources management; Support materials; Training exercise; User Modelling; Web based, Adaptive systems; Curricula; E-learning; Electronic commerce; Knowledge based systems, Planning},
address = {Xi'an},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani2005343,
author = {Milani, A. and Suriani, S. and Marcugini, S.},
title = {Evolutionary online services},
journal = {ACM International Conference Proceeding Series},
year = {2005},
volume = {113},
pages = {343-349},
doi = {10.1145/1089551.1089614},
note = {Conference of 7th International Conference on Electronic Commerce, ICEC05 ; Conference Date: 15 August 2005 Through 17 August 2005; Conference Code:80710},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77953814750&doi=10.1145%2f1089551.1089614&partnerID=40&md5=b065013481490e533042ea67481e907f},
abstract = {This paper present a technique based on genetic algorithms for generating online adaptive services. Online adaptive systems provide flexible services to a mass of clients/users for maximizing some system goals; they dynamically adapt the form and the content of the issued services while the population of clients evolve over time. The idea of online genetic algorithms (online GAs) is to use the online clients response behavior as a fitness function in order to produce the next generation of services. The principle implemented in online GAs, "the application environment is the fitness", allow to model highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behavior of this approach seems to be very relevant and promising for applications characterized by highly dynamical features such as in the web domain (online newspapers, e-markets, websites and advertising engines). Nevertheless the proposed technique has a more general aim for application environments characterized by a massive number of anonymous clients/users which require personalized services, such as in the case of many new IT applications. Copyright 2005 ACM.},
author_keywords = {adaptive models; evolutionary computation; genetic algorithms; online consumer behavior},
keywords = {Adaptive behavior; Adaptive models; Adaptive services; Application environment; Dynamical features; E-markets; evolutionary computation; Evolutionary computations; Evolutionary domain; Fitness functions; Flexible service; IT applications; On-line service; Online consumer behavior; Online newspaper; Personalized service; Response behavior; Web domains, Adaptive systems; Computation theory; Electronic commerce; Function evaluation; Genetic algorithms; Websites, Online systems},
address = {Xi'an},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2005444,
author = {Milani, A. and Marcugini, S.},
title = {An architecture for evolutionary adaptive Web systems},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2005},
volume = {3828 LNCS},
pages = {444-454},
doi = {10.1007/11600930_44},
note = {Conference of 1st International Workshop on Internet and Network Economics, WINE 2005 ; Conference Date: 15 December 2005 Through 17 December 2005; Conference Code:67467},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-33744930843&doi=10.1007%2f11600930_44&partnerID=40&md5=47a94282f7927675fa826f883542815a},
abstract = {This paper present an architecture based on evolutionary genetic algorithms for generating online adaptive services. Online adaptive systems provide flexible services to a mass of clients/users for maximising some system goals, they dynamically adapt the form and the content of the issued services while the population of clients evolve over time. The idea of online genetic algorithms (online GAs) is to use the online clients response behaviour as a fitness function in order to produce the next generation of services. The principle implemented in online GAs, "the application environment is the fitness", allow to model highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behaviour of this approach seems to be very relevant and promising for applications characterised by highly dynamical features such as in the web domain (online newspapers, e-markets, websites and advertising engines). Nevertheless the proposed technique has a more general aim for application environments characterised by a massive number of anonymous clients/users which require personalised services, such as in the case of many new IT applications. © Springer-Verlag Berlin Heidelberg 2005.},
keywords = {Computer architecture; Electronic commerce; Genetic algorithms; Internet; Marketing; Websites; World Wide Web, Anonymous clients; E-markets; Fitness function; Online adaptive systems, Adaptive systems},
address = {Hong Kong},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Marcugini2005139,
author = {Marcugini, S. and Milani, A. and Pambianco, F.},
title = {Maximal (n, 3)-arcs in PG(2,13)},
journal = {Discrete Mathematics},
year = {2005},
volume = {294},
number = {1-2},
pages = {139-145},
doi = {10.1016/j.disc.2004.04.043},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-17644413575&doi=10.1016%2fj.disc.2004.04.043&partnerID=40&md5=f1209159774ad116de7c5b3a98f4ab9b},
abstract = {In this paper we show, using a computer-based search exploiting relations of inclusion between arcs and (n,3)-arcs and projective equivalence properties, that the largest size of a complete (n,3)-arc in PG(2,13) is 23 and that only seven non-equivalent (23,3)-arcs exist. From this result, we deduce the non-existence of some [n,k,n-k]13 linear codes and bounds on the minimum distance of some [n,3,d]13 linear codes. Moreover, we determine the spectrum of the sizes of the complete (n,3)-arcs in PG(2,13) and the classification of the smallest complete (n,3)-arcs. © 2005 Published by Elsevier B.V.},
author_keywords = {(n, 3)-arcs; NMDS codes; Projective spaces},
keywords = {Algorithms; Computational complexity; Computational geometry; Problem solving; Search engines; Set theory; Spectrum analysis; Theorem proving; Vectors, (n,3)-arcs; Galois fields; Near-MDS (NMDS) codes; Projective spaces, Codes (symbols)},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2005709,
author = {Milani, A.},
title = {Minimal knowledge anonymous user profiling for personalized services},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2005},
volume = {3533 LNAI},
pages = {709-711},
doi = {10.1007/11504894_98},
note = {Conference of 18th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems: Innovations in Applied Artificial Intelligence, IEA/AIE 2005 ; Conference Date: 22 June 2005 Through 24 June 2005; Conference Code:67065},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-26944499767&doi=10.1007%2f11504894_98&partnerID=40&md5=94beaf7ad02727982a93369dc215784c},
abstract = {An algorithmic and formal method is presented for automatic profiling of anonymous internet users. User modelling represents a relevant problem in most internet successful user services, such as news sites or search engines, where only minimal knowledge about the user is given, i.e. information such as user session, user tracing and click-stream analysis is not available. On the other hand the ability of giving a personalised response, i.e. tailored on the user preferences and expectations, represents a key factor for successful online services. The proposed model uses the notion of fuzzy similarities in order to match the user observed knowledge with appropriate target profiles. We characterize fuzzy similarity in the theoretical framework of Lukasiewicz structures which guaranties the formal correctness of the approach. The presented model for user profiling with minimal knowledge has many applications, from generation of banners for online advertising to dynamical response pages for public services. © Springer-Verlag Berlin Heidelberg 2005.},
keywords = {Computer simulation; Internet; Marketing; Online searching; Search engines, Click-stream analysis; Lukasiewicz structures, Fuzzy sets},
publisher = {Springer Verlag},
address = {Bari},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2005306,
author = {Milani, A. and Baioletti, M. and Poggioni, V.},
title = {Goal directed Web services},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2005},
volume = {3528 LNAI},
pages = {306-312},
doi = {10.1007/11495772_48},
note = {Conference of Third International Atlantic Web Intelligence Conference on Advances in Web Intelligence, AWIC 2005 ; Conference Date: 6 June 2005 Through 9 June 2005; Conference Code:67064},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-26944431967&doi=10.1007%2f11495772_48&partnerID=40&md5=8fee47eb235dc9ee135d615fc379162c},
abstract = {In this paper a system for goal directed integration of web services based on automated planning is presented. The increasing number of web services available on the net poses the problem of having efficient tools in order to integrate existing services for obtaining complex services which reflect user goals and needs. In this scenario, automated planning techniques represent promising components of such dynamical and evolutionary systems. In the proposed architectural model, web services and user goals are modeled as planning operators and goals, while the generated solution plans are used for directly generating web service scripts. An extended planning model based on the notion of output variable has been introduced in order to take into account of results produced by services invocations. A technique called semantic wrapper has been developed for modeling services as operators. The implementation of P4WS, a planner with output variables which demonstrated the model is described and experimental results are presented. © Springer-Verlag Berlin Heidelberg 2005.},
keywords = {Automation; Computer simulation; Computer software; Evolutionary algorithms; Search engines; Web browsers, Automated planning techniques; Dynamical and evolutionary systems; Goal directed integration; Semantic wrapper; Web services, World Wide Web},
publisher = {Springer Verlag},
address = {Lodz},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Marcugini2004179,
author = {Marcugini, S. and Milani, A. and Pambianco, F.},
title = {Classification of the (n, 3)-arcs in PG(2, 7)},
journal = {Journal of Geometry},
year = {2004},
volume = {80},
number = {1-2},
pages = {179-184},
doi = {10.1007/s00022-004-1777-4},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-55449129900&doi=10.1007%2fs00022-004-1777-4&partnerID=40&md5=8d0c4d5912aed8a86c2cf45418bbecb7},
abstract = {In this paper the classification of the (n, 3)-arcs in PG(2, 7) is presented. It has been obtained using a computer-based exhaustive search that exploits projective equivalence and produces exactly one representative of each equivalence class. For each (n, 3)-arc, the automorphism group and the maximal size of a contained k-arc have been found. © Birkhäuser Verlag, Basel, 2004.},
author_keywords = {(n,3)-arcs; Computer search; Projective plane},
document_type = {Article},
source = {Scopus}
}
@conference{Milani2004779,
author = {Milani, A. and Suriani, S.},
title = {ADAN: Adaptive newspapers based on evolutionary programming},
journal = {Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004},
year = {2004},
pages = {779-780},
doi = {10.1109/WI.2004.10021},
note = {Conference of Proceedings - IEEE/WIC/ACM International Conference on Web Intelligence, WI 2004 ; Conference Date: 20 September 2004 Through 24 September 2004; Conference Code:64424},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-15544363628&doi=10.1109%2fWI.2004.10021&partnerID=40&md5=cf6c281c029f2d32dfe68eec6a564dae},
abstract = {This work presents AdaN an online adaptive newspaper system based on evolutionary programming. Online adaptive newspapers provide flexible services and news to a mass of clients/users for maximizing some system goals, they dynamically adapt the form and the content of the newspaper while the population of clients evolve over time. The techniques of online evolutionary programming (or online GAs) used in ADAN exploits the online clients response behavior as a fitness function in order to produce the next generation of services. The principle implemented in online GAs, "the application environment is the fitness", allow to model highly evolutionary domains where both services providers and clients change and evolve over time. The flexibility and the adaptive behavior of this approach seems to be very relevant and promising for applications characterized by highly dynamical features such as in the web domain (online newspapers, e-markets, websites and advertising engines). © 2004 IEEE.},
keywords = {Journal editors; Online evolutionary programming; Online newspapers; Service providers, Adaptive algorithms; Customer satisfaction; Electronic commerce; File editors; Genetic algorithms; Information retrieval systems; Information technology; Online systems, Evolutionary algorithms},
sponsors = {IEEE Computer Society; Web Intelligence Consortium, WIC; Association for Computing Machinery},
address = {Beijing},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Milani2004563,
author = {Milani, A. and Poggioni, V.},
title = {Action reasoning with uncertain resources},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2004},
volume = {3046 LNCS},
number = {PART 4},
pages = {563-573},
doi = {10.1007/978-3-540-24768-5_60},
note = {Conference of International Conference on Computational Science and Its Applications, ICCSA 2004 ; Conference Date: 14 May 2004 Through 17 May 2004; Conference Code:79386},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-77949742839&doi=10.1007%2f978-3-540-24768-5_60&partnerID=40&md5=34353e7989e0150e34633fa0f2352480},
abstract = {In this paper we present RDPPlan, an automated problem solver which generates plans of actions in order to satisfy logical goals and numerical goals on uncertain resources. Planning with resources is a component of many applications which range from robot planning to automated manufacturing and automatic software composition. In the classical planning model the actions describe purely logical state transitions; some extensions have been recently proposed in order to manage numerical resources which can be produced/consumed in exact amounts. Unfortunately in real domains it is impossible to make accurate and exact previsions about resource production/consumption because of the inherent uncertainty of real world. The planning model introduced in RDPPlan allows to manage uncertainty about the initial value of resources and actions that can make uncertain updates of numerical resources. The proposed model uses the notion of trapezoidal fuzzy intervals to handle the uncertainty on resource values; the solving algorithm extends, for fuzzy resources, the propagation rules of the planner DPPlan. © Springer-Verlag Berlin Heidelberg 2004.},
author_keywords = {Artificial intelligence; Fuzzy sets; Planning; Problem solving},
keywords = {Application programs; Artificial intelligence; Fuzzy sets; Planning; Robot programming, Automated Manufacturing; Classical planning; Plans of actions; Problem solvers; Propagation rule; Software composition; Solving algorithm; Uncertain resource, Problem solving},
sponsors = {'Queen's University of Belfast'; et al.; Heuchera Technologies; University of Calgary; University of Minnesota; University of Perugia},
publisher = {Springer Verlag},
address = {Assisi},
document_type = {Article},
source = {Scopus}
}
@article{Milani2004433,
author = {Milani, A. and Morici, C. and Niewiadomski, R.},
title = {Fuzzy matching of user profiles for a banner engine},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2004},
volume = {3045},
pages = {433-442},
doi = {10.1007/978-3-540-24767-8_45},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-26944431698&doi=10.1007%2f978-3-540-24767-8_45&partnerID=40&md5=14b79871adc4f2beadba24cc78bc5f3f},
abstract = {Most advertisement systems widely used in Internet try to improve advertisement process by targeting specific groups of potential customers. Many systems exploit the information directly provided by the user and the data collected by monitoring user activities in order to built accurate user profiles, which determines the success of the advertisement process. This paper presents a solution to the problem of targeting advertisement information when minimal knowledge about anonymous internet user is given. In particulary as, for example, in the case of search engines, the user remains anonymous and his interaction with the service can be very limited. In this case the information about him is sparse and based only on the keywords and the data submitted by the HTTP request. The proposed architecture is based on the use of predefined profiles and the computation of fuzzy similarities in order to match the observed user with appropriate target profiles. The notion of fuzzy similarity presented here is based on the theoretical framework of the Lukasiewicz structure, which guarantees the correctness of the approach. © Springer-Verlag Berlin Heidelberg 2004.},
author_keywords = {E-commerce; Fuzzy similarity; Online Advertisement; Search Engine; Soft Computing; User Profiling},
keywords = {Electronic commerce; Fuzzy logic; Internet; Search engines; Soft computing, Advertisement informations; Fuzzy similarity; Internet users; Online advertisements; Potential customers; Proposed architectures; Theoretical framework; User profiling, HTTP},
publisher = {Springer Verlag},
document_type = {Article},
source = {Scopus}
}
@conference{Baioletti2003592,
author = {Baioletti, M. and Milani, A. and Poggioni, V.},
title = {Planning with uncertain resources},
journal = {Proceedings of the International Conference on Artificial Intelligence IC-AI 2003},
year = {2003},
volume = {2},
pages = {592-597},
note = {Conference of Proceedings of the International Conference on Artificial Intelligence, IC-AI 2003 ; Conference Date: 23 June 2003 Through 26 June 2003; Conference Code:62570},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-1642326517&partnerID=40&md5=78b5b20ced5db9aab84b0e16396e653f},
abstract = {In this paper a model for planning with uncertain resources represented with fuzzy intervals is presented. Nearly ali existing models of planning with resource require to specify exact values for updating resources modified by actions execution. In other words these models cannot deal with more realistic situations in which the resources quantities are not completely known. The presented model allows to manage domains more tailored to real world, where preconditions and effects over resources can be specified by uncertain intervals using fuzzy sets, in addition mixed logical/quantitative and pure numerical goals can be posed. The fuzzy approach adequately represents the kind of uncertainty existing in planning domains, in this context the choice of trapezoidal fuzzy intervals represents a solution which combine a simple representation with computationally simplicity. It is, also, presented a search strategy for goals over resources that provides a specific method to guide search. This strategy is necessary when solving "pure numerical problems". The presented model is independent from the planner, experimental results shows that the implementation of the model as extension of DPPlan, called RDPPlan, does not decrease its efficiency.},
author_keywords = {Fuzzy sets; Planning; Uncertainty},
keywords = {Fuzzy sets; Optimization; Problem solving; Semantics, Fuzzy intervals; Non directional search algorithm; Plan generation phase; Resources management, Planning},
address = {Las Vegas, NV},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti2003336,
author = {Baioletti, M. and Milani, A. and Poggioni, V.},
title = {Planning with fuzzy resources},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {2003},
volume = {2829},
pages = {336-348},
doi = {10.1007/978-3-540-39853-0_28},
note = {Conference of 8th Congress of the Italian Association for Artificial Intelligence ; Conference Date: 23 September 2003 Through 26 September 2003; Conference Code:118429},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-7444271864&doi=10.1007%2f978-3-540-39853-0_28&partnerID=40&md5=25b17f46f393cb4efe5082f4f7f92056},
abstract = {In this paper a model for planning with fuzzy resources is presented. Nearly all existing models of planning with resources need to work with exact value of the resources modified by actions execution. Therefore these models cannot deal with more realistic situations in which the resources quantities are not completely known. The model presented here allows to manage domains more tailored to real world, where preconditions and effects over resources can be specified in terms of uncertain intervals using fuzzy sets. Moreover it is possible to define problems with mixed logical/quantitative and pure numerical goals. The fuzzy approach adequately represents the kind of uncertainty existing in planning domains. The choice of trapezoidal fuzzy intervals represents a solution which combine a simple, but expressive representation, with computational simplicity. It is also presented a search strategy for goals over resources that provides a specific method to guide search. This strategy is necessary when solving “pure numerical problems”. Finally some experimental results are presented and commented. © Springer-Verlag Berlin Heidelberg 2003.},
keywords = {Computer science; Computers; Artificial intelligence; Computational methods; Online searching; Problem solving; Resource allocation; Strategic planning, Fuzzy approach; Fuzzy interval; Numerical problems; Planning domains; Real-world; Search strategies, Artificial intelligence; Fuzzy sets, Action execution; Fuzzy intervals; Fuzzy resources; Resource modification},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Marcugini2002963,
author = {Marcugini, S. and Milani, A. and Pambianco, F.},
title = {NMDS codes of maximal length over Fq, 8 ≤ q ≤ 11},
journal = {IEEE Transactions on Information Theory},
year = {2002},
volume = {48},
number = {4},
pages = {963-966},
doi = {10.1109/18.992802},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036540699&doi=10.1109%2f18.992802&partnerID=40&md5=a98177d2af342e2d284caeec34723ddf},
abstract = {A linear [n, k, d]q code C is called near maximum-distance separable (NMDS) if d(C) = n - k and d(C⊥ = k. The maximum length of an NMDS [n, k, d]q code is denoted by m′(k, q). In this correspondence, it has been verified by a computer-based proof that m′(5, 8) = 15, m′(4, 9) = 16, m′(5, 9) = 16, and 20 ≤ m′(4, 11) ≤ 21. Moreover, the NMDS codes of length m′(4, 8), m'(5, 8), and m′(4, 9) have been classified. As the dual code of an NMDS code is NMDS, the values of m′(k, 8), k = 10, 11, 12, and of m′(k, 9), k = 12, 13, 14 have been also deduced.},
author_keywords = {Galois fields; Linear codes; Near maximum-distance separable (NMDS) codes},
keywords = {Boundary conditions; Computer simulation; Error correction; Matrix algebra; Signal detection; Theorem proving, Linear codes; Near maximum-distance separable (NMDS) codes, Codes (symbols)},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti200211,
author = {Baioletti, M. and Capotorti, A. and Tulipani, S. and Vantaggi, B.},
title = {Simplification rules for the coherent probability assessment problem},
journal = {Annals of Mathematics and Artificial Intelligence},
year = {2002},
volume = {35},
number = {1-4},
pages = {11-28},
doi = {10.1023/A:1014585822798},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0036104568&doi=10.1023%2fA%3a1014585822798&partnerID=40&md5=f57acb61d475d781f06d14b8ec76b954},
abstract = {In this paper we develop a procedure for checking the consistency (coherence) of a partial probability assessment. The general problem (called CPA) is NP-complete, hence, to have a reasonable application some heuristic is needed. Our proposal differs from others because it is based on a skilful use of the logical relations present among the events. In other approaches the consistency problem is reduced directly to the satisfiability of a system of linear constraints. Here, thanks to the characterization of particular configurations and to the elimination of variables, an instance of the problem is reduced to smaller instances. To obtain such results, we introduce a procedure based on rules resembling those given by Davis-Putnam for the satisfiability of Boolean formulas. At the end a particularized description of an actual implementation is given.},
author_keywords = {Coherent probability assessment; Probabilistic satisfiability; Simplification rules},
document_type = {Article},
source = {Scopus}
}
@article{Marcugini2001263,
author = {Marcugini, S. and Milani, A. and Pambianco, F.},
title = {Classification of the [n, 3, n - 3]q NMDS codes over GF(7), GF(8) and GF(9)},
journal = {Ars Combinatoria},
year = {2001},
volume = {61},
pages = {263-269},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0348238533&partnerID=40&md5=8ce398e7ba0b286d51e399a7f2f30e3a},
abstract = {A linear [n, k, d]q code C is called NMDS if d(C) = n - k and d(C⊥) = k. In this paper the classification of the [n, 3, n - k]q NMDS codes is given for q = 7, 8, 9. It has been found using the correspondence between [n, 3, n - k]q NMDS codes and (n, 3)-arcs of PG(2, q).},
document_type = {Article},
source = {Scopus}
}
@article{Marcugini1999421,
author = {Marcugini, S. and Milani, A. and Pambianco, F.},
title = {Maximal (n, 3)-arcs in PG(2, 11)},
journal = {Discrete Mathematics},
year = {1999},
volume = {208-209},
pages = {421-426},
doi = {10.1016/S0012-365X(99)00202-2},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0009017751&doi=10.1016%2fS0012-365X%2899%2900202-2&partnerID=40&md5=f10aa193bf9dc31c61955dc77c847b56},
abstract = {In this paper we determine the largest size of a complete (n, 3)-arc in PG(2, 11). By a computer-based exhaustive search that exploits the fact that an (n, 3)-arc with n ≥21 contains an arc of size 7 and that uses projective equivalence properties, we show that the largest size of an (n, 3)-arc in PG(2, 11) is 21 and that only two non-equivalent (21, 3)-arcs exist. © 1999 Elsevier Science B.V. All rights reserved.},
publisher = {Elsevier},
document_type = {Article},
source = {Scopus}
}
@article{Faina1998235,
author = {Faina, G. and Marcugini, S. and Milani, A. and Pambianco, F.},
title = {The sizes k of the complete k-caps in PG(n, q), for small q and 3 ≤ n ≤ 5},
journal = {Ars Combinatoria},
year = {1998},
volume = {50},
pages = {235-243},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0032413381&partnerID=40&md5=a115465fc5e83e600214549920bc8a11},
abstract = {It is known that there exists a one-to-one correspondence between the classes of equivalent [n, n - k, 4]-codes over GF(q) and the classes of projectively equivalent complete n-caps in PG(k - 1, q) (see [20], [40]). Hence all results on caps can be translated in terms of such codes. This fact stimulated many researches on the fundamental problem of determining the spectrum of the values of k for which there exist complete k-caps in PG(n, q). This paper reports the result of a computer search for the spectrum of k's that occur as a size of a complete k-cap in some finite projective spaces. The full catalog of such sizes k is given in the following projective spaces: PG(3, q),for q ≤ 5, PG(4, 2), PG(4, 3), PG(5, 2). Concrete examples of such caps are presented for each possible k.*.},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti199839,
author = {Baioletti, M. and Marcugini, S. and Milani, A.},
title = {An extension of SATPLAN for planning with constraints},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {1998},
volume = {1480 LNAI},
pages = {39-49},
doi = {10.1007/bfb0057433},
note = {Conference of 8th International Conference on Artificial Intelligence: Methodology, Systems, and Applications, AIMSA 1998 ; Conference Date: 21 September 1998 Through 23 September 1998; Conference Code:93537},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84867774376&doi=10.1007%2fbfb0057433&partnerID=40&md5=0f2b7bce0b4d5ab04cc6a5c2c1de2995},
abstract = {In this paper we present C-SATPLAN, a planner which realizes an extension to the satisfiability based planning system SATPLAN for solving constrained planning problems, whose architecture is independent from the SAT solver algorithm being used. C-SATPLAN is able to manage general planning constraints expressed in PCDL, a language which has been introduced in a previous work of the authors [2]. PCDL constraints are defined in terms of a quantified predicate over plan steps and facts, and can express several kinds of planning constraints as achievement goals, activity goals, presence or absence of operators, precedence and codesignation constraints. Former results about PCDL [2] showed that constraints belonging to a significant sublanguage (PCL-1) of PCDL can be compiled within the planning domain, i.e. there exists an effective procedure which produces a new planning domain whose solutions solve the original constrained planning problem. Therefore PCL-1 planning problems can be solved with an ordinary planner after a translation phase. In this paper we show that solving general constrained planning problems requires the extension of SATPLAN, a planning approach for unconstrained domains based on the equivalence between satisfiability and classical unconstrained planning [7]. The C-SATPLAN extension exploits the feature that planning constraints can be encoded as additional clauses in the clausal representation of the planning problem. This method is independent from the SAT solver engine used, therefore any SAT solver can be used to solve a constrained planning problem. Following this approach the architecture of the constrained planning system C-SATPLAN, composed by three interacting modules, has been designed and implemented. The first module takes as input a planning problem, produces a planning graph and finally translates it as a SAT instance. The second module generates the additional component of the SAT instance by translating the PCDL constraint in clausal form. The final module incorporates two different SAT solver engines which are able to produce the solutions, if any, of the original constrained planning problem by proving the satisfiability of the clausal instance.},
keywords = {Artificial intelligence; Computer architecture; Engines; Model checking, Planning domains; Planning graphs; Planning problem; Planning systems; SAT instances; SAT solvers; Satisfiability, C (programming language)},
sponsors = {Eur. Coord. Comm. Artif. Intell. (ECCAI)},
publisher = {Springer Verlag},
address = {Sozopol},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Faina19973,
author = {Faina, G. and Marcugini, S. and Milani, A. and Pambianco, F.},
title = {The spectrum of the values k for which there exists a complete k-arc in PG(2, q) for q ≤ 23},
journal = {Ars Combinatoria},
year = {1997},
volume = {47},
pages = {3-11},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0038874011&partnerID=40&md5=1a8661a4c383014affdab216829e9336},
abstract = {Arcs and linear maximum distance separable (M.D. S.) codes are equivalent objects. Hence, all results on arcs can be expressed in terms of linear M.D.S. codes and conversely. The list of all complete k-arcs in PG(2,q) has been previously determined for q ≤ 16. In this paper, (i) all values of k for which there exists a complete k-arc in PG(2, q), with 17 ≤ q ≤ 23, are determined; (ii) a complete k-arc for each such possible k is exhibited.},
document_type = {Article},
source = {Scopus}
}
@article{Baioletti1997311,
author = {Baioletti, M. and Marcugini, S. and Milani, A.},
title = {Compiling task networks into partial order planning domains},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {1997},
volume = {1321},
pages = {311-321},
doi = {10.1007/3-540-63576-9_118},
note = {Conference of 5th Congress of the Italian Association for Artificial Intelligence, AI*IA 1997 ; Conference Date: 17 September 1997 Through 19 September 1997; Conference Code:149359},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84961386653&doi=10.1007%2f3-540-63576-9_118&partnerID=40&md5=2d608179af57c532c06e65fb35e0bd56},
abstract = {This paper presents theoretical results and techniques for representing and managing task network goals in the framework of partial order planning. Task oriented formalisms are more expressive than partial order based formalism for problem goals in dynamical and changing domains, but they are not more powerful. We prove that it is always possible to express a task network problem in terms of an equivalent problem stated in partial order planning formalism. The task network model has been extended to describe external events (EETN), a feature not present in many planning models. The equivalence between this new model and PO formalism is also proved. These results allow to reuse existing partial order planners as tools in order to solve task network goals. We introduce a linear cost technique of domain transformation which compiles a given task domain in an equivalent operator based domain which is then submitted to a nonlinear planner. This technique has been successfully demonstrated by the implementation of a EETN planner based on domain tranfornnations for UCPOP. © Springer-Verlag Berlin Heidelberg 1997.},
keywords = {Artificial intelligence; Linear transformations, Domain transformation; Equivalent operators; Partial order; Partial order planners; Partial order planning; Planning models; Task network modeling; Task-oriented, Mathematical transformations},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti199752,
author = {Baioletti, M. and Marcugini, S. and Milani, A.},
title = {Task planning and partial order planning: A domain transformation approach},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {1997},
volume = {1348 LNAI},
pages = {52-63},
doi = {10.1007/3-540-63912-8_75},
note = {Conference of 4th European Conference on Planning, ECP 1997 ; Conference Date: 24 September 1997 Through 26 September 1997; Conference Code:104575},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84898686360&doi=10.1007%2f3-540-63912-8_75&partnerID=40&md5=216372de87e890e04ae467653e53a460},
abstract = {In this paper 1 we introduce techniques of domain transformation for representing and managing task network goals in the framework of partial order planning. A task network planning model, extended to describe external events, is introduced. We prove that it is always possible to express a task network problem in terms of an equivalent problem stated in partial order planning formalism on an appropriate domain. A linear cost technique of domain transformation is described: a given task domain is compiled to generate an equivalent operator based domain which is then submitted to a nonlinear planner. This result shows how to reuse existing partial order planners for solving task network problems. This technique has been successfully demonstrated by the implementation of two TN planners based on domain tranformation for UCPOP and for GRAPHPLAN.},
author_keywords = {Domain transformation; Expressivity; Partial order planning; Task planning},
keywords = {Linear transformations; Planning, Domain transformation; Equivalent operators; Expressivity; Partial order planners; Partial order planning; Task domain; Task networks; Task planning, Mathematical transformations},
publisher = {Springer Verlag},
address = {Toulouse},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Baioletti1995291,
author = {Baioletti, M. and Marcugini, S. and Milani, A.},
title = {A weakest precondition semantics for conditional planning},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {1995},
volume = {992},
pages = {291-302},
doi = {10.1007/3-540-60437-5_29},
note = {Conference of 4th Congress of the Italian Association for Artificial Intelligence, AI*IA 1995 ; Conference Date: 11 October 1995 Through 13 October 1995; Conference Code:150669},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84957703101&doi=10.1007%2f3-540-60437-5_29&partnerID=40&md5=aa91a73d27294ec35522356b376e04b9},
abstract = {In this paper we show an approach to conditional planning which is based on a particular three valued logic. Assignments and conditional formulae (built by means of the alternate operator as introduced in [7]) are used to represent uncertain situations. A model for actions in a conditional framework is defined by giving an execution function, which returns the updated situation after the execution, and an executability predicate. We also define a weakest precondition semantics in order to determine the least alternative situation in which a plan is executable and, after the execution, a required formula holds. The tools we introduced allow us to compile a plan in a macroaetion, which is an abstraction of a plan, neglecting its internal decomposition. It is possible to prove that the use of macroactions is correct in a more complex plan. © Springer-Verlag Berlin Heidelberg 1995.},
keywords = {Artificial intelligence; Semantics, Conditional planning; Three-valued logic; Weakest precondition, Many valued logics},
sponsors = {Comitato Scienze d’ingegneria e Architettura e Comitato Scienze e Tecnologia dell'informazione, Consiglio Nazionale delle Ricerche},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani1994305,
author = {Milani, A.},
title = {Minimizing sensors task in robot plan monitoring},
journal = {Proceedings of the 7th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1994},
year = {1994},
pages = {305-314},
note = {Conference of 7th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 1994 ; Conference Date: 31 May 1994 Through 3 June 1994; Conference Code:129422},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85053710290&partnerID=40&md5=a4ceeed1103157f98cba9821cfedfd5f},
sponsors = {ACM Special Interest Group on Artificial Intelligence (SIGAI); Am Assoc for Artifical Intelligence (AAAI); Computer Society (IEEE-CS); EECIA; Intl Soc of Applied Science; Japanese Society for Artifical Intelligence (JSAI)},
publisher = {Association for Computing Machinery, Inc},
document_type = {Conference Paper},
source = {Scopus}
}
@conference{Milani1992291,
author = {Milani, Alfredo and Terragnolo, Maurizio},
title = {Representing conflicts in parallel planning},
year = {1992},
pages = {291-292},
doi = {10.1016/b978-0-08-049944-4.50048-3},
note = {Conference of Proceedings of the 1st International Conference on Artificial Intelligence Planning Systems ; Conference Date: 15 June 1992 Through 17 June 1992; Conference Code:17018},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-0026998494&doi=10.1016%2fb978-0-08-049944-4.50048-3&partnerID=40&md5=f643a03930f50b136551f53652b0dc9c},
abstract = {The notion of Affected and Protected clause extends classical action models to enable a more reliable composition of parallel nonatomic actions. A notion of legal action description is given. On the basis of the given model conditions are stated in order to allo analysis of conflicts in parallel and nonlinear planning.},
keywords = {Artificial intelligence; Nonlinear equations, Action models; Conflicts representation; Nonlinear planning; Parallel planning, Planning},
sponsors = {American Assoc for Artificial Intelligence; Defense Advanced Research Projects Agency; Univ of Maryland Inst for Advanced Computer Studies},
publisher = {Publ by Morgan Kaufmann Publ Inc, Los Altos},
address = {College Park, MD, USA},
document_type = {Conference Paper},
source = {Scopus}
}
@article{Fringuelli1991430,
author = {Fringuelli, B. and Marcugini, S. and Milani, A. and Rivoira, S.},
title = {Truth maintenance in approximate reasoning},
journal = {Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)},
year = {1991},
volume = {549 LNAI},
pages = {430-434},
doi = {10.1007/3-540-54712-6_256},
note = {Conference of 2nd Congress of the Italian Association for Artificial Intelligence, AI*IA 1991 ; Conference Date: 29 October 1991 Through 31 October 1991; Conference Code:169489},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85031791288&doi=10.1007%2f3-540-54712-6_256&partnerID=40&md5=735c1f8849ad61e796230bcd5c669070},
abstract = {A reason maintenance system which extends an ATMS through Mukaidono’s fuzzy logic is described. It supports a problem solver in situations affected by incomplete information and vague data, by allowing nonmonotonic inferences and the revision of previous conclusions when contradictions are detected. © Springer-Verlag Berlin Heidelberg 1991.},
keywords = {Artificial intelligence, Approximate reasoning; Incomplete information; It supports; Maintenance systems; Non-monotonic inference; Problem solvers; Truth maintenance; Vague data, Fuzzy logic},
sponsors = {},
publisher = {Springer Verlag},
document_type = {Conference Paper},
source = {Scopus}
}
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