Publications

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Journal Article
P. Mukala, Cerone, A., and Turini, F., An empirical verification of a-priori learning models on mailing archives in the context of online learning activities of participants in free\libre open source software (FLOSS) communities, Education and Information Technologies, vol. 22, pp. 3207–3229, 2017.
P. Contucci, Panizzi, E., Ricci-Tersenghi, F., and Sirbu, A., Egalitarianism in the rank aggregation problem: a new dimension for democracy, Quality & Quantity, pp. 1–16, 2015.
A. Baroni, Conte, A., Patrignani, M., and Ruggieri, S., Efficiently Clustering Very Large Attributed Graphs, arXiv preprint arXiv:1703.08590, 2017.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., Efficient breadth-first mining of frequent pattern with monotone constraints, Knowl. Inf. Syst., vol. 8, pp. 131-153, 2005.
A. Rossi, Pappalardo, L., Cintia, P., F Iaia, M., Fernàndez, J., and Medina, D., Effective injury forecasting in soccer with GPS training data and machine learning, PloS one, vol. 13, p. e0201264, 2018.
R. Portocarre Sarmento, Lemos, L., Cordeiro, M., Rossetti, G., and Cardoso, D., DynComm R Package–Dynamic Community Detection for Evolving Networks, arXiv preprint arXiv:1905.01498, 2019.
A. Brogi, Renso, C., and Turini, F., Dynamic composition of parameterised logic modules, Comput. Lang., vol. 25, pp. 211-242, 1999.
A. Brogi, Renso, C., and Turini, F., Dynamic Composition of Parameterised Logic Modules, Computer Languages, pp. 211–242, 1999.
M. Nanni, Trasarti, R., Monreale, A., Grossi, V., and Pedreschi, D., Driving Profiles Computation and Monitoring for Car Insurance CRM, Journal ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, pp. 14:1–14:26, 2016.
G. Calogiuri, Johansen, P. Foss, Rossi, A., and Thurston, M., Do “girls just wanna have fun”? Participation trends and motivational profiles of women in Norway’s ultimate mass participation ski event, Frontiers in Psychology, vol. 10, p. 2548, 2019.
A. Romei, Ruggieri, S., and Turini, F., Discrimination discovery in scientific project evaluation: A case study, Expert Systems with Applications, vol. 40, pp. 6064–6079, 2013.
S. Hajian, Domingo-Ferrer, J., Monreale, A., Pedreschi, D., and Giannotti, F., Discrimination- and privacy-aware patterns, Data Min. Knowl. Discov., vol. 29, pp. 1733–1782, 2015.
R. Trasarti, Olteanu-Raimond, A. - M., Nanni, M., Couronné, T., Furletti, B., Giannotti, F., Smoreda, Z., and Ziemlicki, C., Discovering urban and country dynamics from mobile phone data with spatial correlation patterns, Telecommunications Policy, p. -, 2014.
S. Rinzivillo, Mainardi, S., Pezzoni, F., Coscia, M., Giannotti, F., and Pedreschi, D., Discovering the Geographical Borders of Human Mobility, KI - Künstliche Intelligenz, 2012.
R. Guidotti, Gabrielli, L., Monreale, A., Pedreschi, D., and Giannotti, F., Discovering temporal regularities in retail customers’ shopping behavior, EPJ Data Science, vol. 7, p. 6, 2018.
B. Furletti, Trasarti, R., Cintia, P., and Gabrielli, L., Discovering and Understanding City Events with Big Data: The Case of Rome, Information, vol. 8, p. 74, 2017.
C. R. Daniel Ornellana, Developing a Spatial Knowledge Representation for Pedestrian Interactions, 2009.
S. Bruestle, Pappalardo, L., and Guidotti, R., Defining Geographic Markets from Probabilistic Clusters: A Machine Learning Algorithm Applied to Supermarket Scanner Data, Available at SSRN 3452058, 2019.
M. Aldinucci, Ruggieri, S., and Torquati, M., Decision tree building on multi-core using FastFlow, Concurrency and Computation: Practice and Experience, vol. 26, pp. 800–820, 2014.
F. Giannotti and Pedreschi, D., Datalog with Non-Deterministic Choice Computers NDB-PTIME, J. Log. Program., vol. 35, pp. 79-101, 1998.
L. Pappalardo and Simini, F., Data-driven generation of spatio-temporal routines in human mobility, Data Mining and Knowledge Discovery, 2017.
D. Janssens, Giannotti, F., Nanni, M., Pedreschi, D., and Rinzivillo, S., Data Science for Simulating the Era of Electric Vehicles, KI - Künstliche Intelligenz, 2012.
R. Pellungrini, Pappalardo, L., Pratesi, F., and Monreale, A., A Data Mining Approach to Assess Privacy Risk in Human Mobility Data, ACM Trans. Intell. Syst. Technol., vol. 9, pp. 31:1–31:27, 2017.
A. Sirbu, Crane, M., and Ruskin, H. J., Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks, Microarrays, vol. 4, pp. 255–269, 2015.
A. Monreale, Trasarti, R., Pedreschi, D., Renso, C., and Bogorny, V., C-safety: a framework for the anonymization of semantic trajectories, Transactions on Data Privacy, vol. 4, pp. 73-101, 2011.

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