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F. Giannotti, Naretto, F., and Bodria, F., Explainable for Trustworthy AI, in Human-Centered Artificial Intelligence - Advanced Lectures, 18th European Advanced Course on AI, ACAI 2021, Berlin, Germany, October 11-15, 2021, extended and improved lecture notes, 2021.
F. Giannotti, Raffaetà, A., Renso, C., and Turini, F., Complex Reasoning on Geographical Data, in SEBD, 2001, pp. 331-338.
F. Giannotti, Gozzi, C., and Manco, G., Clustering Transactional Data, in SEBD, 2001, pp. 163-176.
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, 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, Invited talk: Logical Data Mining Query Languages, in KDID, 2002, p. 1.
F. Giannotti and Manco, G., LDL-M$_{\mbox{ine}}$: Integrating Data Mining with Intelligent Query Answering, in JELIA, 2002, pp. 517-520.
F. Giannotti, Raffaetà, A., Renso, C., and Turini, F., Complex Reasoning on Geographical Data, in SEBD, 2001, pp. 331-338.
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, 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, 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, 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, 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, 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.
R. Guidotti and Cintia, P., Towards a Boosted Route Planner Using Individual Mobility Models, in Software Engineering and Formal Methods, Springer Berlin Heidelberg, 2015, pp. 108–123.
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.

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