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R. Guidotti, Monreale, A., Nanni, M., Giannotti, F., and Pedreschi, D., Clustering Individual Transactional Data for Masses of Users, in Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 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 and Coscia, M., On the Equivalence Between Community Discovery and Clustering, in International Conference on Smart Objects and Technologies for Social Good, 2017.
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, Coscia, M., Pedreschi, D., and Pennacchioli, D., Behavioral Entropy and Profitability in Retail, in IEEE International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015), Paris, 2015.
R. Guidotti, Nanni, M., Rinzivillo, S., Pedreschi, D., and Giannotti, F., Never drive alone: Boosting carpooling with network analysis, Information Systems, vol. 64, pp. 237–257, 2017.
R. Guidotti, Gabrielli, L., Monreale, A., Pedreschi, D., and Giannotti, F., Discovering temporal regularities in retail customers’ shopping behavior, EPJ Data Science, vol. 7, p. 6, 2018.
R. Guidotti, Rossetti, G., Pappalardo, L., Giannotti, F., and Pedreschi, D., Next Basket Prediction using Recurring Sequential Patterns, arXiv preprint arXiv:1702.07158, 2017.
R. Guidotti, Monreale, A., Ruggieri, S., Pedreschi, D., Turini, F., and Giannotti, F., Local Rule-Based Explanations of Black Box Decision Systems, 2018.
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., Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences, IEEE Transactions on Knowledge and Data Engineering, 2018.
R. Guidotti and Rossetti, G., “Know Thyself” How Personal Music Tastes Shape the Last. Fm Online Social Network, in International Symposium on Formal Methods, 2019.
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, Monreale, A., Rinzivillo, S., Pedreschi, D., and Giannotti, F., Retrieving Points of Interest from Human Systematic Movements, in Software Engineering and Formal Methods, Springer International Publishing, 2014, pp. 294–308.
R. Guidotti, Mobility Ranking - Human Mobility Analysis Using Ranking Measures, 2013.
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.
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.
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.

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