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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, Nanni, M., and Pedreschi, D., Efficient Mining of Temporally Annotated Sequences, in SDM, 2006.
F. Giannotti, Gozzi, C., and Manco, G., Clustering Transactional Data, in SEBD, 2001, pp. 163-176.
F. Giannotti, Nanni, M., Pedreschi, D., and Pinelli, F., Mining sequences with temporal annotations, in SAC, 2006, pp. 593-597.
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, 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, Gozzi, C., and Manco, G., Clustering Transactional Data, in PKDD, 2002, pp. 175-187.
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, Invited talk: Logical Data Mining Query Languages, in KDID, 2002, p. 1.
F. Giannotti, Raffaetà, A., Renso, C., and Turini, F., Complex Reasoning on Geographical Data, in SEBD, 2001, pp. 331-338.
F. Giannotti and Manco, G., LDL-M$_{\mbox{ine}}$: Integrating Data Mining with Intelligent Query Answering, in JELIA, 2002, pp. 517-520.
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., and Rinzivillo, S., Learning Data Mining, in 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), 2018.
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, 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 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.

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