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F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., Query Answering in Nondeterministic, Nonmonotonic Logic Databases, in FQAS, 1998, pp. 175-187.
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.
F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., Synthetic generation of cellular network positioning data, in GIS, 2005, pp. 12-20.
F. Giannotti, Manco, G., and Turini, F., Specifying Mining Algorithms with Iterative User-Defined Aggregates, IEEE Trans. Knowl. Data Eng., vol. 16, pp. 1232-1246, 2004.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., On the Effective Semantics of Nondeterministic, Nonmonotonic, Temporal Logic Databases, in CSL, 1998, pp. 58-72.
F. Giannotti, Gabrielli, L., Pedreschi, D., and Rinzivillo, S., Understanding human mobility with big data, in Solving Large Scale Learning Tasks. Challenges and Algorithms, Springer International Publishing, 2016, pp. 208–220.
F. Giannotti, Manco, G., Nanni, M., Pedreschi, D., and Turini, F., Integration of Deduction and Induction for Mining Supermarket Sales Data, in SEBD, 1999, pp. 117-131.
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, Manco, G., and Turini, F., Towards a Logic Query Language for Data Mining, in Database Support for Data Mining Applications, 2004, pp. 76-94.
F. Giannotti and Manco, G., Querying Inductive Databases via Logic-Based User-Defined Aggregates, in PKDD, 1999, pp. 125-135.
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.
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, 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, 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, Rossetti, G., Pappalardo, L., Giannotti, F., and Pedreschi, D., Market Basket Prediction using User-Centric Temporal Annotated Recurring Sequences, in 2017 IEEE International Conference on Data Mining (ICDM), 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, 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.

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