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F. Giannotti, Manco, G., and Turini, F., “Towards a Logic Query Language for Data Mining”, in Database Support for Data Mining Applications, 2004, pp. 76-94.
F. Giannotti and Manco, G., “Querying Inductive Databases via Logic-Based User-Defined Aggregates”, in PKDD, 1999, pp. 125-135.
F. Giannotti and Pedreschi, D., Mobility, Data Mining and Privacy - Geographic Knowledge Discovery. Springer, 2008.
F. Giannotti, Nanni, M., Pedreschi, D., and Pinelli, F., “Trajectory pattern analysis for urban traffic”, in Second International Workshop on Computational Transportation Science, SEATTLE, USA, 2009, pp. 43-47.
F. Giannotti, Pedreschi, D., and Turini, F., “Mobility, Data Mining and Privacy the Experience of the GeoPKDD Project”, in PinKDD, 2008, pp. 25-32.
F. Giannotti, Jeansoulin, R., and Theodoridis, Y., “Beyond Current Technology: The Perspective of Three EC GIS Projects”, in DEXA Workshop, 1999, p. 510.
F. Giannotti, Matteucci, A., Pedreschi, D., and Turini, F., “Symbolic Evaluation with Structural Recursive Symbolic Constants”, Sci. Comput. Program., vol. 9, pp. 161-177, 1987.
F. Giannotti and Pedreschi, D., “Mobility, Data Mining and Privacy: A Vision of Convergence”, in Mobility, Data Mining and Privacy, 2008, pp. 1-11.
F. Giannotti and Manco, G., “Querying inductive Databases via Logic-Based user-defined aggregates”, in APPIA-GULP-PRODE, 1999, pp. 605-620.
F. Giannotti, Nanni, M., Pedreschi, D., Pinelli, F., Renso, C., Rinzivillo, S., and Trasarti, R., “Unveiling the complexity of human mobility by querying and mining massive trajectory data”, VLDB J., vol. 20, pp. 695-719, 2011.
F. Giannotti and Pedreschi, D., “Declarative Semantics for Pruning Operators in Logic Programming”, in LPNMR, 1990, pp. 27-37.
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, 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.
R. Guidotti and Ruggieri, S., “On The Stability of Interpretable Models”, in 2019 International Joint Conference on Neural Networks (IJCNN), 2019.

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