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F. Giannotti, Pedreschi, D., and Theodoridis, Y., “Geographic privacy-aware knowledge discovery and delivery”, in EDBT, 2009, pp. 1157-1158.
F. Giannotti, Pedreschi, D., Saccà, D., and Zaniolo, C., “Non-Determinism in Deductive Databases”, in DOOD, 1991, pp. 129-146.
F. Giannotti and Manco, G., “Making Knowledge Extraction and Reasoning Closer”, in PAKDD, 2000, pp. 360-371.
F. Giannotti and Latella, D., “Using Abstract Interpretation for Gate splitting in LOTOS Specifications”, in WSA, 1992, pp. 194-204.
F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., “Synthetic generation of cellular network positioning data”, in GIS, 2005, pp. 12-20.
F. Giannotti and Manco, G., “Declarative Knowledge Extraction with Interactive User-Defined Aggregates”, in FQAS, 2000, pp. 435-444.
F. Giannotti, Nanni, M., Pedreschi, D., Renso, C., Rinzivillo, S., and Trasarti, R., “GeoPKDD – Geographic Privacy-aware Knowledge Discovery”, in The European Future Technologies Conference (FET 2009), 2009.
F. Giannotti, Naretto, F., and Bodria, F., “Explainable for Trustworthy AI”, in Human-Centered Artificial Intelligence - Advanced Lectures, 18th European Advanced Course on AI, ACAI 2021, Berlin, Germany, October 11-15, 2021, extended and improved lecture notes, 2021.
F. Giannotti, Nanni, M., Pedreschi, D., Renso, C., and Trasarti, R., “Mining Mobility Behavior from Trajectory Data”, in CSE (4), 2009, pp. 948-951.
F. Giannotti, Nanni, M., and Pedreschi, D., “Logic-Based Knowledge Discovery in Databases”, in EJC, 2000, pp. 279-283.
F. Giannotti and Pedreschi, D., Mobility, Data Mining and Privacy - Geographic Knowledge Discovery. Springer, 2008.
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, Monreale, A., Rinzivillo, S., Pedreschi, D., and Giannotti, F., “Unveiling mobility complexity through complex network analysis”, Social Network Analysis and Mining, vol. 6, p. 59, 2016.
R. Guidotti, Trasarti, R., Nanni, M., Giannotti, F., and Pedreschi, D., “There's A Path For Everyone: A Data-Driven Personal Model Reproducing Mobility Agendas”, in 4th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2017), Tokyo, 2017.
R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., “Factual and Counterfactual Explanations for Black Box Decision Making”, IEEE Intelligent Systems, 2019.
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, Soldani, J., Neri, D., Brogi, A., and Pedreschi, D., “Helping your docker images to spread based on explainable models”, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2018.

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