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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, Gozzi, C., and Manco, G., “Clustering Transactional Data”, in PKDD, 2002, pp. 175-187.
F. Giannotti, “Invited talk: Logical Data Mining Query Languages”, in KDID, 2002, p. 1.
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 Manco, G., “LDL-M$_{\mbox{ine}}$: Integrating Data Mining with Intelligent Query Answering”, in JELIA, 2002, pp. 517-520.
F. Giannotti, Nanni, M., Pinelli, F., and Pedreschi, D., “Trajectory pattern mining”, in KDD, 2007, pp. 330-339.
F. Giannotti, Raffaetà, A., Renso, C., and Turini, F., “Complex Reasoning on Geographical Data”, in SEBD, 2001, pp. 331-338.
F. Giannotti, Pedreschi, D., and Theodoridis, Y., “Geographic privacy-aware knowledge discovery and delivery”, in EDBT, 2009, pp. 1157-1158.
F. Giannotti, Gozzi, C., and Manco, G., “Characterizing Web User Accesses: A Transactional Approach to Web Log Clustering”, in ITCC, 2002, p. 312.
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, Greco, S., Saccà, D., and Zaniolo, C., “Programming with Non-Determinism in Deductive Databases”, Ann. Math. Artif. Intell., vol. 19, pp. 97-125, 1997.
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.
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.
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, 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.
R. Guidotti, Rossetti, G., and Pedreschi, D., “Audio Ergo Sum”, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2016.
R. Guidotti, Monreale, A., and Cariaggi, L., “Investigating Neighborhood Generation Methods for Explanations of Obscure Image Classifiers”, in Pacific-Asia Conference on Knowledge Discovery and Data Mining, 2019.
R. Guidotti and Ruggieri, S., “On The Stability of Interpretable Models”, in 2019 International Joint Conference on Neural Networks (IJCNN), 2019.

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