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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.
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, 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, Monreale, A., and Pedreschi, D., “The AI black box Explanation Problem”, ERCIM NEWS, pp. 12–13, 2019.
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, 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, 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, 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.
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, 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 Gabrielli, L., “Recognizing Residents and Tourists with Retail Data Using Shopping Profiles”, in International Conference on Smart Objects and Technologies for Social Good, 2017.
R. Guidotti and Ruggieri, S., “On The Stability of Interpretable Models”, in 2019 International Joint Conference on Neural Networks (IJCNN), 2019.
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, 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, 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, Rossetti, G., and Pedreschi, D., “Audio Ergo Sum”, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2016.
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, 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.
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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