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Author Title [ Type(Desc)] Year
Journal Article
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.
C. R. Daniel Ornellana, Developing a Spatial Knowledge Representation for Pedestrian Interactions, 2009.
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.
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.
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. 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. 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.
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.
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.
A. Brogi, Renso, C., and Turini, F., Dynamic Composition of Parameterised Logic Modules, Computer Languages, pp. 211–242, 1999.
A. Brogi, Renso, C., and Turini, F., Dynamic composition of parameterised logic modules, Comput. Lang., vol. 25, pp. 211-242, 1999.
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.
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. Baroni, Conte, A., Patrignani, M., and Ruggieri, S., Efficiently Clustering Very Large Attributed Graphs, arXiv preprint arXiv:1703.08590, 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.
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.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., Evolving networks: Eras and turning points, Intell. Data Anal., vol. 17, pp. 27–48, 2013.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., Exante: A Preprocessing Method for Frequent-Pattern Mining, IEEE Intelligent Systems, vol. 20, pp. 25-31, 2005.
G. Rossetti, Milli, L., Giannotti, F., and Pedreschi, D., Forecasting success via early adoptions analysis: A data-driven study, PloS one, vol. 12, p. e0189096, 2017.
M. Fayzullin, Nanni, M., Pedreschi, D., and Subrahmanian, V. S., Foundations of distributed interaction systems, Ann. Math. Artif. Intell., vol. 28, pp. 127-168, 2000.
I. Martinucci, Natilli, M., Lorenzoni, V., Pappalardo, L., Monreale, A., Turchetti, G., Pedreschi, D., Marchi, S., Barale, R., and de Bortoli, N., Gastroesophageal reflux symptoms among Italian university students: epidemiology and dietary correlates using automatically recorded transactions, BMC gastroenterology, vol. 18, p. 116, 2018.
F. Giannotti and Latella, D., Gate Splitting in LOTOS Specifications Using Abstract Interpretation, Sci. Comput. Program., vol. 23, pp. 127-149, 1994.
R. Prieto Curiel, Pappalardo, L., Gabrielli, L., and Bishop, S. Richard, Gravity and scaling laws of city to city migration, PLOS ONE, vol. 13, pp. 1-19, 2018.
G. Rossetti, Pappalardo, L., Kikas, R., Pedreschi, D., Giannotti, F., and Dumas, M., Homophilic network decomposition: a community-centric analysis of online social services, Social Network Analysis and Mining, vol. 6, p. 103, 2016.
C. Renso, Baglioni, M., de Macêdo, J. Antônio F., Trasarti, R., and Wachowicz, M., How you move reveals who you are: understanding human behavior by analyzing trajectory data, Knowl. Inf. Syst., vol. 37, pp. 331–362, 2013.

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