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F. Giannotti and Latella, D., Gate Splitting in LOTOS Specifications Using Abstract Interpretation, in TAPSOFT, 1993, pp. 437-452.
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, Nanni, M., Pedreschi, D., and Pinelli, F., Mining sequences with temporal annotations, in SAC, 2006, pp. 593-597.
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.
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, 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, Monreale, A., and Pedreschi, D., The AI black box Explanation Problem, ERCIM NEWS, pp. 12–13, 2019.
R. Guidotti, Coscia, M., Pedreschi, D., and Pennacchioli, D., Going Beyond GDP to Nowcast Well-Being Using Retail Market Data, in Advances in Network Science, Springer International Publishing, 2016, pp. 29–42.
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, 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 and Berlingerio, M., Where Is My Next Friend? Recommending Enjoyable Profiles in Location Based Services, in Complex Networks VII, Springer International Publishing, 2016, pp. 65–78.
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, 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 Ruggieri, S., On The Stability of Interpretable Models, in 2019 International Joint Conference on Neural Networks (IJCNN), 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, 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, 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.

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