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F. Giannotti, Lakshmanan, L. V. S., Monreale, A., Pedreschi, D., and Wang, H. Wendy, “Privacy-preserving data mining from outsourced databases.”, in the 3rd International Conference on Computers, Privacy, and Data Protection: An element of choice , 2011.
F. Giannotti and Latella, D., “Gate Splitting in LOTOS Specifications Using Abstract Interpretation”, in TAPSOFT, 1993, pp. 437-452.
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, Manco, G., Nanni, M., and Pedreschi, D., “Nondeterministic, Nonmonotonic Logic Databases”, IEEE Trans. Knowl. Data Eng., vol. 13, pp. 813-823, 2001.
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, 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.
F. Giannotti, Gozzi, C., and Manco, G., “Clustering Transactional Data”, in SEBD, 2001, pp. 163-176.
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, Manco, G., and Turini, F., “Specifying Mining Algorithms with Iterative User-Defined Aggregates: A Case Study”, in PKDD, 2001, pp. 128-139.
F. Giannotti, Trasarti, R., Bontcheva, K., and Grossi, V., “SoBigData: Social Mining & Big Data Ecosystem”, in Companion of the The Web Conference 2018 on The Web Conference 2018, 2018.
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, 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.
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.
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, Coscia, M., Pedreschi, D., and Pennacchioli, D., “Behavioral Entropy and Profitability in Retail”, in IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015), Paris, 2015.
R. Guidotti, Monreale, A., Nanni, M., Giannotti, F., and Pedreschi, D., “Clustering Individual Transactional Data for Masses of Users”, in Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017.
R. Guidotti, Monreale, A., Ruggieri, S., Naretto, F., Turini, F., Pedreschi, D., and Giannotti, F., “Stable and actionable explanations of black-box models through factual and counterfactual rules”, Data Mining and Knowledge Discovery, 2022.
R. Guidotti and Coscia, M., “On the Equivalence Between Community Discovery and Clustering”, in International Conference on Smart Objects and Technologies for Social Good, 2017.
R. Guidotti, Sassi, A., Berlingerio, M., Pascale, A., and Ghaddar, B., “Social or green? A data-driven approach for more enjoyable carpooling”, in Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on, 2015.

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