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F. Giannotti, Nanni, M., and Pedreschi, D., “Logic-Based Knowledge Discovery in Databases”, in EJC, 2000, pp. 279-283.
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.
F. Giannotti and Latella, D., “Gate Splitting in LOTOS Specifications Using Abstract Interpretation”, in TAPSOFT, 1993, pp. 437-452.
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, Manco, G., Nanni, M., and Pedreschi, D., “Nondeterministic, Nonmonotonic Logic Databases”, IEEE Trans. Knowl. Data Eng., vol. 13, pp. 813-823, 2001.
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., Pinelli, F., Renso, C., Rinzivillo, S., and Trasarti, R., “Mobility data mining: discovering movement patterns from trajectory data”, in Computational Transportation Science, 2010, pp. 7-10.
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, Lakshmanan, L. V. S., Monreale, A., Pedreschi, D., and Wang, H. Wendy, “Privacy-Preserving Mining of Association Rules From Outsourced Transaction Databases”, IEEE Systems Journal, 2013.
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, 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.
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.
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., 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., Pappalardo, L., Giannotti, F., and Pedreschi, D., “Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences”, IEEE Transactions on Knowledge and Data Engineering, 2018.
R. Guidotti and Ruggieri, S., “Assessing the Stability of Interpretable Models”, arXiv preprint arXiv:1810.09352, 2018.
R. Guidotti, Soldani, J., Neri, D., and Brogi, A., “Explaining successful docker images using pattern mining analysis”, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2018.
R. Guidotti and Rossetti, G., ““Know Thyself” How Personal Music Tastes Shape the Last.Fm Online Social Network”, in Formal Methods. FM 2019 International Workshops, Cham, 2020.

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