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F. Giannotti, Pedreschi, D., Saccà, D., and Zaniolo, C., Non-Determinism in Deductive Databases, in DOOD, 1991, pp. 129-146.
F. Giannotti, Nanni, M., Pedreschi, D., Renso, C., and Trasarti, R., Mining Mobility Behavior from Trajectory Data, in CSE (4), 2009, pp. 948-951.
F. Giannotti and Manco, G., Making Knowledge Extraction and Reasoning Closer, in PAKDD, 2000, pp. 360-371.
F. Giannotti and Latella, D., Using Abstract Interpretation for Gate splitting in LOTOS Specifications, in WSA, 1992, pp. 194-204.
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, Mazzoni, A., Puntoni, S., and Renso, C., Synthetic generation of cellular network positioning data, in GIS, 2005, pp. 12-20.
F. Giannotti and Manco, G., Declarative Knowledge Extraction with Interactive User-Defined Aggregates, in FQAS, 2000, pp. 435-444.
F. Giannotti, Nanni, M., and Pedreschi, D., Logic-Based Knowledge Discovery in Databases, in EJC, 2000, pp. 279-283.
F. Giannotti and Latella, D., Gate Splitting in LOTOS Specifications Using Abstract Interpretation, in TAPSOFT, 1993, pp. 437-452.
F. Giannotti, Pedreschi, D., and Zaniolo, C., Semantics and Expressive Power of Nondeterministic Constructs in Deductive Databases, J. Comput. Syst. Sci., vol. 62, pp. 15-42, 2001.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., Nondeterministic, Nonmonotonic Logic Databases, IEEE Trans. Knowl. Data Eng., vol. 13, pp. 813-823, 2001.
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, 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.
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, Mobility Ranking - Human Mobility Analysis Using Ranking Measures, 2013.
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.
R. Guidotti, Rossetti, G., and Pedreschi, D., Audio Ergo Sum, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2016.
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.

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