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F. Giannotti, Nanni, M., Pedreschi, D., Pinelli, F., Renso, C., Rinzivillo, S., and Trasarti, R., “Unveiling the complexity of human mobility by querying and mining massive trajectory data”, VLDB J., vol. 20, pp. 695-719, 2011.
F. Giannotti and Pedreschi, D., “Datalog with Non-Deterministic Choice Computers NDB-PTIME”, J. Log. Program., vol. 35, pp. 79-101, 1998.
F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., “Synthetic generation of cellular network positioning data”, in GIS, 2005, pp. 12-20.
F. Giannotti, Manco, G., and Turini, F., “Specifying Mining Algorithms with Iterative User-Defined Aggregates”, IEEE Trans. Knowl. Data Eng., vol. 16, pp. 1232-1246, 2004.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., “Query Answering in Nondeterministic, Nonmonotonic Logic Databases”, in FQAS, 1998, pp. 175-187.
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. Giannotti, Manco, G., Nanni, M., Pedreschi, D., and Turini, F., “Integration of Deduction and Induction for Mining Supermarket Sales Data”, in SEBD, 1999, pp. 117-131.
F. Giannotti, Manco, G., and Turini, F., “Towards a Logic Query Language for Data Mining”, in Database Support for Data Mining Applications, 2004, pp. 76-94.
F. Giannotti and Manco, G., “Querying Inductive Databases via Logic-Based User-Defined Aggregates”, in PKDD, 1999, pp. 125-135.
F. Giannotti, Nanni, M., Pinelli, F., and Pedreschi, D., “Trajectory pattern mining”, in KDD, 2007, pp. 330-339.
F. Giannotti, Pedreschi, D., and Theodoridis, Y., “Geographic privacy-aware knowledge discovery and delivery”, in EDBT, 2009, pp. 1157-1158.
P. Gravino, Sirbu, A., Becker, M., Servedio, V. D. P., and Loreto, V., “Experimental Assessment of the Emergence of Awareness and Its Influence on Behavioral Changes: The Everyaware Lesson”, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 337–362.
P. Gravino, Caminiti, S., Sirbu, A., Tria, F., Servedio, V. D. P., and Loreto, V., “Unveiling Political Opinion Structures with a Web-experiment”, in Proceedings of the 1st International Conference on Complex Information Systems, 2016.
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.
V. Grossi, Monreale, A., Nanni, M., Pedreschi, D., and Turini, F., “Clustering Formulation Using Constraint Optimization”, in Software Engineering and Formal Methods - {SEFM} 2015 Collocated Workshops: ATSE, HOFM, MoKMaSD, and VERY*SCART, York, UK, September 7-8, 2015, Revised Selected Papers, 2015.
V. Grossi, Romei, A., and Ruggieri, S., “A Case Study in Sequential Pattern Mining for IT-Operational Risk”, in ECML/PKDD (1), 2008, pp. 424-439.
V. Grossi, Pedreschi, D., and Turini, F., “Data Mining and Constraints: An Overview”, in Data Mining and Constraint Programming, Springer International Publishing, 2016, pp. 25–48.
V. Grossi, Romei, A., and Turini, F., “Survey on using constraints in data mining”, Data Mining and Knowledge Discovery, vol. 31, pp. 424–464, 2017.
B. Guidi, Michienzi, A., and Rossetti, G., “Towards the dynamic community discovery in decentralized online social networks”, Journal of Grid Computing, vol. 17, pp. 23–44, 2019.
B. Guidi, Michienzi, A., and Rossetti, G., “Dynamic community analysis in decentralized online social networks”, in European Conference on Parallel Processing, 2017.
R. Guidotti and Rossetti, G., ““Know Thyself” How Personal Music Tastes Shape the Last.Fm Online Social Network”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.
R. Guidotti and Gabrielli, L., “Recognizing Residents and Tourists with Retail Data Using Shopping Profiles”, in International Conference on Smart Objects and Technologies for Social Good, 2017.
R. Guidotti, Monreale, A., Rinzivillo, S., Pedreschi, D., and Giannotti, F., “Retrieving Points of Interest from Human Systematic Movements”, in Software Engineering and Formal Methods, Springer International Publishing, 2014, pp. 294–308.
R. Guidotti, Monreale, A., and Pedreschi, D., “The AI black box Explanation Problem”, ERCIM NEWS, pp. 12–13, 2019.
R. Guidotti, Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., and Pedreschi, D., “A survey of methods for explaining black box models”, ACM computing surveys (CSUR), vol. 51, p. 93, 2018.

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