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R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., Factual and Counterfactual Explanations for Black Box Decision Making, IEEE Intelligent Systems, 2019.
S. Hajian, Monreale, A., Pedreschi, D., Domingo-Ferrer, J., and Giannotti, F., Fair pattern discovery, in Symposium on Applied Computing, {SAC} 2014, Gyeongju, Republic of Korea - March 24 - 28, 2014, 2014, pp. 113–120.
M. Berlingerio, Coscia, M., and Giannotti, F., Finding and Characterizing Communities in Multidimensional Networks, in ASONAM, 2011, pp. 490-494.
M. Berlingerio, Coscia, M., and Giannotti, F., Finding redundant and complementary communities in multidimensional networks, in CIKM, 2011, pp. 2181-2184.
G. Rossetti, Milli, L., Giannotti, F., and Pedreschi, D., Forecasting success via early adoptions analysis: A data-driven study, PloS one, vol. 12, p. e0189096, 2017.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., Foundations of Multidimensional Network Analysis, in ASONAM, 2011, pp. 485-489.
L. Pollacci, Guidotti, R., Rossetti, G., Giannotti, F., and Pedreschi, D., The Fractal Dimension of Music: Geography, Popularity and Sentiment Analysis, in International Conference on Smart Objects and Technologies for Social Good, 2018.
L. Pollacci, Guidotti, R., Rossetti, G., Giannotti, F., and Pedreschi, D., The Fractal Dimension of Music: Geography, Popularity and Sentiment Analysis, in International Conference on Smart Objects and Technologies for Social Good, 2017.
F. Bonchi, Giannotti, F., and Pedreschi, D., Frequent Pattern Queries for Flexible Knowledge Discovery, in SEBD, 2004, pp. 250-261.
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F. Giannotti and Latella, D., Gate Splitting in LOTOS Specifications Using Abstract Interpretation, Sci. Comput. Program., vol. 23, pp. 127-149, 1994.
F. Giannotti and Latella, D., Gate Splitting in LOTOS Specifications Using Abstract Interpretation, in TAPSOFT, 1993, pp. 437-452.
G. Andrienko, Andrienko, N., Giannotti, F., Monreale, A., Pedreschi, D., and Rinzivillo, S., A Generalisation-based Approach to Anonymising Movement Data, 13th AGILE conference on Geographic Information Science. 2010.
F. Giannotti, Pedreschi, D., and Theodoridis, Y., Geographic privacy-aware knowledge discovery and delivery, in EDBT, 2009, pp. 1157-1158.
F. Giannotti, Nanni, M., Pedreschi, D., Renso, C., Rinzivillo, S., and Trasarti, R., GeoPKDD – Geographic Privacy-aware Knowledge Discovery, in The European Future Technologies Conference (FET 2009), 2009.
M. Nanni, Andrienko, G., Barabasi, A. - L., Boldrini, C., Bonchi, F., Cattuto, C., Chiaromonte, F., Comandé, G., Conti, M., Coté, M., Dignum, F., Dignum, V., Domingo-Ferrer, J., Ferragina, P., Giannotti, F., Guidotti, R., Helbing, D., Kaski, K., Kertész, J., Lehmann, S., Lepri, B., Lukowicz, P., Matwin, S., Jiménez, D. Megías, Monreale, A., Morik, K., Oliver, N., Passarella, A., Passerini, A., Pedreschi, D., Pentland, A., Pianesi, F., Pratesi, F., Rinzivillo, S., Ruggieri, S., Siebes, A., Torra, V., Trasarti, R., van den Hoven, J., and Vespignani, A., Give more data, awareness and control to individual citizens, and they will help COVID-19 containment, 2021.
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., GLocalX - From Local to Global Explanations of Black Box AI Models, vol. 294, p. 103457, 2021.
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P. Cintia, Pappalardo, L., Pedreschi, D., Giannotti, F., and Malvaldi, M., The harsh rule of the goals: data-driven performance indicators for football teams, IEEE International Conference on Data Science and Advanced Analytics. 2015.
O. Abul, Atzori, M., Bonchi, F., and Giannotti, F., Hiding Sensitive Trajectory Patterns, in ICDM Workshops, 2007, pp. 693-698.
O. Abul, Atzori, M., Bonchi, F., and Giannotti, F., Hiding Sequences, in ICDE Workshops, 2007, pp. 147-156.
O. Abul, Atzori, M., Bonchi, F., and Giannotti, F., Hiding Sequences, in SEBD, 2007, pp. 233-241.
G. Rossetti, Pappalardo, L., Kikas, R., Pedreschi, D., Giannotti, F., and Dumas, M., Homophilic network decomposition: a community-centric analysis of online social services, Social Network Analysis and Mining, vol. 6, p. 103, 2016.
G. Amato, Candela, L., Castelli, D., Esuli, A., Falchi, F., Gennaro, C., Giannotti, F., Monreale, A., Nanni, M., Pagano, P., Pappalardo, L., Pedreschi, D., Pratesi, F., Rabitti, F., Rinzivillo, S., Rossetti, G., Ruggieri, S., Sebastiani, F., and Tesconi, M., How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science, in A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, S. Flesca, Greco, S., Masciari, E., and Saccà, D., Eds. Cham: Springer International Publishing, 2018, pp. 287 - 306.

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