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R. G. Pensa
,
Monreale, A.
,
Pinelli, F.
, and
Pedreschi, D.
,
“
Pattern-Preserving k-Anonymization of Sequences and its Application to Mobility Data Mining
”
, in
PiLBA
, 2008.
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V. Grossi
,
Guns, T.
,
Monreale, A.
,
Nanni, M.
, and
Nijssen, S.
,
“
Partition-Based Clustering Using Constraint Optimization
”
, in
Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach
, Springer International Publishing, 2016, pp. 282–299.
DOI
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A. Sirbu
,
Becker, M.
,
Caminiti, S.
,
De Baets, B.
,
Elen, B.
,
Francis, L.
,
Gravino, P.
,
Hotho, A.
,
Ingarra, S.
,
Loreto, V.
,
Molino, A.
,
Mueller, J.
,
Peters, J.
,
Ricchiuti, F.
,
Saracino, F.
,
Servedio, V. D. P.
,
Stumme, G.
,
Theunis, J.
,
Tria, F.
, and
Van den Bossche, J.
,
“
Participatory Patterns in an International Air Quality Monitoring Initiative.
”
,
PLoS One
, vol. 10, p. e0136763, 2015.
PubMed
DOI
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O
D. Pennacchioli
,
Coscia, M.
, and
Pedreschi, D.
,
“
Overlap versus partition: marketing classification and customer profiling in complex networks of products
”
, in
Data engineering workshops (ICDEW), 2014 IEEE 30th international conference on
, 2014.
DOI
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M. Coscia
,
Rinzivillo, S.
,
Pedreschi, D.
, and
Giannotti, F.
,
“
Optimal Spatial Resolution for the Analysis of Human Mobility
”
,
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
. Instanbul, Turkey, 2012.
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A. Sirbu
,
Loreto, V.
,
Servedio, V. D. P.
, and
Tria, F.
,
“
Opinion dynamics with disagreement and modulated information
”
,
Journal of Statistical Physics
, pp. 1–20, 2013.
DOI
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A. Sirbu
,
Loreto, V.
,
Servedio, V. D. P.
, and
Tria, F.
,
“
Opinion dynamics: models, extensions and external effects
”
, in
Participatory Sensing, Opinions and Collective Awareness
, Springer, 2017, pp. 363–401.
DOI
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C. Toccaceli
,
Milli, L.
, and
Rossetti, G.
,
“
Opinion Dynamic Modeling of Fake News Perception
”
, in
International Conference on Complex Networks and Their Applications
, 2020.
DOI
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D. Aquilino
,
Asirelli, P.
,
Renso, C.
, and
Turini, F.
,
“
An Operator for Composing Deductive Databases with Theories of Constraints
”
, pp. 57–70, 1995.
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D. Aquilino
,
Asirelli, P.
,
Renso, C.
, and
Turini, F.
,
“
An Operator for Composing Deductive Databases with Theories of Constraints
”
, in
LPNMR
, 1995, pp. 57-70.
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D. Pedreschi
,
Giannotti, F.
,
Guidotti, R.
,
Monreale, A.
,
Pappalardo, L.
,
Ruggieri, S.
, and
Turini, F.
,
“
Open the Black Box Data-Driven Explanation of Black Box Decision Systems
”
, 2018.
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M. Baglioni
,
Giovannetti, E.
,
Masserotti, M. V.
,
Renso, C.
, and
Spinsanti, L.
,
“
Ontology-driven Querying of Geographical Databases
”
, pp. 31–44, 2008.
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B. Furletti
,
Bellandi, A.
,
Grossi, V.
, and
Romei, A.
,
“
Ontology-Driven Association Rule Extraction: A Case Study
”
, in
International Workshop on Contexts and Ontologies: Representation and Reasoning
, Roskilde, Denmark, 2007.
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M. Baglioni
,
Bellandi, A.
,
Furletti, B.
,
Spinsanti, L.
, and
Turini, F.
,
“
Ontology-Based Business Plan Classification
”
, in
EDOC
, 2008, pp. 365-371.
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F. Turini
,
Furletti, B.
,
Baglioni, M.
,
Spinsanti, L.
, and
Bellandi, A.
,
“
Ontology-Based Business Plan Classification
”
, in
Enterprise Distributed Object Computing Conference (EDOC)
, 2008.
DOI
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M. Baglioni
,
de Macêdo, J. A. F.
,
Renso, C.
, and
Wachowicz, M.
,
“
An Ontology-Based Approach for the Semantic Modelling and Reasoning on Trajectories
”
, in
ER Workshops
, 2008, pp. 344-353.
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B. Furletti
,
“
Ontology Driven Knowledge Discovery
”
, IMT - Lucca, Lucca - Italy, 2009.
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B. Furletti
,
Bellandi, A.
,
Grossi, V.
, and
Romei, A.
,
“
Ontological Support for Association Rule Mining
”
, in
IASTED International Conference on Artificial Intelligence and Applications (AIA)
, Innsbruck, Austria , 2008.
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P. Mukala
,
Cerone, A.
, and
Turini, F.
,
“
Ontolifloss: Ontology for learning processes in FLOSS communities
”
, in
International Conference on Software Engineering and Formal Methods
, 2014.
DOI
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N
G. Rossetti
,
Pappalardo, L.
, and
Rinzivillo, S.
,
“
A novel approach to evaluate community detection algorithms on ground truth
”
, in
7th Workshop on Complex Networks
, Dijon, France, 2016.
DOI
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F. Giannotti
,
Manco, G.
,
Nanni, M.
, and
Pedreschi, D.
,
“
Nondeterministic, Nonmonotonic Logic Databases
”
,
IEEE Trans. Knowl. Data Eng.
, vol. 13, pp. 813-823, 2001.
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D. Pedreschi
and
Subrahmanian, V. S.
,
“
Non-determinism in Deductive Databases - Preface
”
,
Ann. Math. Artif. Intell.
, vol. 19, pp. 1-2, 1997.
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F. Giannotti
,
Pedreschi, D.
,
Saccà, D.
, and
Zaniolo, C.
,
“
Non-Determinism in Deductive Databases
”
, in
DOOD
, 1991, pp. 129-146.
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G. Rossetti
,
Pedreschi, D.
, and
Giannotti, F.
,
“
Node-centric Community Discovery: From static to dynamic social network analysis
”
,
Online Social Networks and Media
, vol. 3, pp. 32–48, 2017.
DOI
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R. Guidotti
,
Rossetti, G.
,
Pappalardo, L.
,
Giannotti, F.
, and
Pedreschi, D.
,
“
Next Basket Prediction using Recurring Sequential Patterns
”
,
arXiv preprint arXiv:1702.07158
, 2017.
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