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D. Bacciu, Bellandi, A., Furletti, B., Grossi, V., and Romei, A., Discovering Strategic Behaviour in Multi- Agent Scenarios by Ontology-Driven Mining, in Advances in Robotics, Automation and Control, 2008.
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.
V. Bacarella, Giannotti, F., Nanni, M., and Pedreschi, D., Discovery of ads web hosts through traffic data analysis, in DMKD, 2004, pp. 76-81.
D. Pedreschi, Ruggieri, S., and Turini, F., The discovery of discrimination, in Discrimination and privacy in the information society, Springer, 2013, pp. 91–108.
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.
D. Pedreschi, Ruggieri, S., and Turini, F., Discrimination-aware data mining, in KDD, 2008, pp. 560-568.
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.
C. Panigutti, Perotti, A., and Pedreschi, D., Doctor XAI: an ontology-based approach to black-box sequential data classification explanations, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
M. Baglioni, Furletti, B., and Turini, F., DrC4.5: Improving C4.5 by means of Prior Knowledge, in ACM Symposium on Applied Computing, Santa Fe, New Mexico, USA, 2005.
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.
B. Guidi, Michienzi, A., and Rossetti, G., Dynamic community analysis in decentralized online social networks, in European Conference on Parallel Processing, 2017.
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.
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. 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. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., On the Effective Semantics of Nondeterministic, Nonmonotonic, Temporal Logic Databases, in CSL, 1998, pp. 58-72.
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.
K. S. Boeg, Ira Assent,, and Magnani, M., Efficient GPU-based skyline computation, in DAMON@SIGMOD 2013, 2013.
F. Giannotti, Nanni, M., and Pedreschi, D., Efficient Mining of Temporally Annotated Sequences, in SDM, 2006.
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.
A. Sirbu, Crane, M., and Ruskin, H. J., EGIA–Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach, in Complex Networks V, Springer International Publishing, 2014, pp. 217–229.