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F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., “Synthetic generation of cellular network positioning data”, in GIS, 2005, pp. 12-20.
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.
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, Pedreschi, D., and Zaniolo, C., “Semantics and Expressive Power of Nondeterministic Constructs in Deductive Databases”, J. Comput. Syst. Sci., vol. 62, pp. 15-42, 2001.
F. Giannotti and Latella, D., “Gate Splitting in LOTOS Specifications Using Abstract Interpretation”, in TAPSOFT, 1993, pp. 437-452.
F. Giannotti, Pedreschi, D., and Turini, F., “Mobility, Data Mining and Privacy the Experience of the GeoPKDD Project”, in PinKDD, 2008, pp. 25-32.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., “Nondeterministic, Nonmonotonic Logic Databases”, IEEE Trans. Knowl. Data Eng., vol. 13, pp. 813-823, 2001.
F. Giannotti and Pedreschi, D., “Mobility, Data Mining and Privacy: A Vision of Convergence”, in Mobility, Data Mining and Privacy, 2008, pp. 1-11.
F. Giannotti, Raffaetà, A., Renso, C., and Turini, F., “Complex Reasoning on Geographical Data”, in SEBD, 2001, pp. 331-338.
F. Giannotti and Latella, D., “Gate Splitting in LOTOS Specifications Using Abstract Interpretation”, Sci. Comput. Program., vol. 23, pp. 127-149, 1994.
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., 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.
R. Guidotti, Monreale, A., Matwin, S., and Pedreschi, D., “Black Box Explanation by Learning Image Exemplars in the Latent Feature Space”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
R. Guidotti, Rossetti, G., and Pedreschi, D., “Audio Ergo Sum”, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2016.

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