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F. Giannotti and Manco, G., Querying inductive Databases via Logic-Based user-defined aggregates, in APPIA-GULP-PRODE, 1999, pp. 605-620.
F. Giannotti and Pedreschi, D., Declarative Semantics for Pruning Operators in Logic Programming, in LPNMR, 1990, pp. 27-37.
F. Giannotti, Manco, G., Pedreschi, D., and Turini, F., Experiences with a Logic-Based Knowledge Discovery Support Environment, in AI*IA, 1999, pp. 202-213.
F. Giannotti, Manco, G., Pedreschi, D., and Turini, F., Experiences with a Logic-based knowledge discovery Support Environment, in 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 1999.
F. Giannotti and Hermenegildo, M. V., A Technique for Recursive Invariance Detection and Selective Program Specification, in PLILP, 1991, pp. 323-334.
F. Giannotti and Manco, G., Making Knowledge Extraction and Reasoning Closer, in PAKDD, 2000, pp. 360-371.
F. Giannotti, Pedreschi, D., Saccà, D., and Zaniolo, C., Non-Determinism in Deductive Databases, in DOOD, 1991, pp. 129-146.
F. Giannotti and Manco, G., Declarative Knowledge Extraction with Interactive User-Defined Aggregates, in FQAS, 2000, pp. 435-444.
F. Giannotti and Latella, D., Using Abstract Interpretation for Gate splitting in LOTOS Specifications, in WSA, 1992, pp. 194-204.
F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., Synthetic generation of cellular network positioning data, in GIS, 2005, pp. 12-20.
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, 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.
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.
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, 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, Rossetti, G., and Pedreschi, D., Audio Ergo Sum, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2016.
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., and Pedreschi, D., The AI black box Explanation Problem, ERCIM NEWS, pp. 12–13, 2019.
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.

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