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H
L. Pappalardo, Barlacchi, G., Pellungrini, R., and Simini, F., “Human Mobility from theory to practice: Data, Models and Applications”, in Companion of The 2019 World Wide Web Conference, WWW 2019, San Francisco, CA, USA, May 13-17, 2019., 2019.
A. Sirbu, Andrienko, G., Andrienko, N., Boldrini, C., Conti, M., Giannotti, F., Guidotti, R., Bertoli, S., Kim, J., Muntean, C. Ioana, Pappalardo, L., Passarella, A., Pedreschi, D., Pollacci, L., Pratesi, F., and Sharma, R., “Human migration: the big data perspective”, International Journal of Data Science and Analytics, pp. 1–20, 2020.
C. Renso, Baglioni, M., de Macêdo, J. Antônio F., Trasarti, R., and Wachowicz, M., “How you move reveals who you are: understanding human behavior by analyzing trajectory data”, Knowl. Inf. Syst., vol. 37, pp. 331–362, 2013.
L. Pappalardo, Rossetti, G., and Pedreschi, D., “"How Well Do We Know Each Other?" Detecting Tie Strength in Multidimensional Social Networks”, in International Conference on Advances in Social Networks Analysis and Mining, {ASONAM} 2012, Istanbul, Turkey, 26-29 August 2012, 2012.
G. Cornacchia, Böhm, M., Mauro, G., Nanni, M., Pedreschi, D., and Pappalardo, L., “How Routing Strategies Impact Urban Emissions”, in Proceedings of the 30th International Conference on Advances in Geographic Information Systems, New York, NY, USA, 2022.
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.
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.
A. Sirbu and Babaoglu, O., “A Holistic Approach to Log Data Analysis in High-Performance Computing Systems: The Case of IBM Blue Gene/Q”, in Euro-Par 2015: parallel Processing Workshops, LNCS 9523, 2015.
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.
O. Abul, Atzori, M., Bonchi, F., and Giannotti, F., “Hiding Sensitive Trajectory Patterns”, in ICDM Workshops, 2007, pp. 693-698.
R. Guidotti, Soldani, J., Neri, D., Brogi, A., and Pedreschi, D., “Helping your docker images to spread based on explainable models”, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2018.
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.
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P. Cintia, Trasarti, R., de Macêdo, J. Antônio F., Almada, L., and Fereira, C., “A Gravity Model for Speed Estimation over Road Network”, in 2013 {IEEE} 14th International Conference on Mobile Data Management, Milan, Italy, June 3-6, 2013 - Volume 2, 2013.
R. Prieto Curiel, Pappalardo, L., Gabrielli, L., and Bishop, S. Richard, “Gravity and scaling laws of city to city migration”, PLOS ONE, vol. 13, pp. 1-19, 2018.
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.
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.
M. Setzu, Guidotti, R., Monreale, A., and Turini, F., “Global Explanations with Local Scoring”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
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.
D. Fadda, Natilli, M., and Rinzivillo, S., “GET-Viz: a library for automatic generation of visual dashboard for geographical time series”, 8th International Conference on Computational Social Science (IC2S2). Chicago, USA, 2022.
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.
F. Giannotti, Pedreschi, D., and Theodoridis, Y., “Geographic privacy-aware knowledge discovery and delivery”, in EDBT, 2009, pp. 1157-1158.
A. Knott, Pedreschi, D., Chatila, R., Chakraborti, T., Leavy, S., Baeza-Yates, R., Eyers, D., Trotman, A., Teal, P. D., Biecek, P., Russell, S., and Bengio, Y., “Generative AI models should include detection mechanisms as a condition for public releaseAbstract”, Ethics and Information Technology, vol. 25, 2023.
G. Mauro, Luca, M., Longa, A., Lepri, B., and Pappalardo, L., “Generating mobility networks with generative adversarial networks”, EPJ data science, vol. 11, p. 58, 2022.
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.

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