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Journal Article
G. Andrienko, Andrienko, N., Hunter, C., Rinzivillo, S., and Wrobel, S., Scalable Analysis of Movement Data for Extracting and Exploring Significant Places, IEEE Transactions on Visualization and Computer Graphics, vol. 19, 2013.
A. Lulli, Gabrielli, L., Dazzi, P., Dell'Amico, M., Michiardi, P., Nanni, M., and Ricci, L., Scalable and flexible clustering solutions for mobile phone-based population indicators, I. J. Data Science and Analytics, vol. 4, pp. 285–299, 2017.
A. Baroni and Ruggieri, S., Segregation discovery in a social network of companies, Journal of Intelligent Information Systems, 2017.
C. Parent, Spaccapietra, S., Renso, C., Andrienko, G., Andrienko, N., Bogorny, V., Damiani M L,, Gkoulalas-Divanis A,, de Macêdo, J. A. F., and Pelekis, N., Semantic Trajectories Modeling and Analysis, ACM Computing Surveys, vol. 45, 2013.
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.
S. Marchetti, Giusti, C., Pratesi, M., Salvati, N., Giannotti, F., Pedreschi, D., Rinzivillo, S., Pappalardo, L., and Gabrielli, L., Small Area Model-Based Estimators Using Big Data Sources, Journal of Official Statistics, vol. 31, pp. 263–281, 2015.
M. Batty, Axhausen, K. W., Giannotti, F., Pozdnoukhov, A., Bazzani, A., Wachowicz, M., Ouzounis, G., and Portugali, Y., Smart cities of the future, European Physical Journal-Special Topics, vol. 214, p. 481, 2012.
G. Andrienko, Andrienko, N., Boldrini, C., Caldarelli, G., Cintia, P., Cresci, S., Facchini, A., Giannotti, F., Gionis, A., Guidotti, R., and others, (So) Big Data and the transformation of the city, International Journal of Data Science and Analytics, 2020.
M. Coscia, Rinzivillo, S., Giannotti, F., and Pedreschi, D., Spatial and Temporal Evaluation of Network-based Analysis of Human Mobility, Social Network Analysis and Mining, vol. to appear, 2013.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., Spatio-Temporal Data, Spatio-Temporal Databases: Flexible Querying and Reasoning, p. 75, 2013.
M. Fiore, Shafiq, Z., Smoreda, Z., Stanica, R., and Trasarti, R., Special Issue on Mobile Traffic Analytics, Computer Communications, vol. 95, pp. 1–2, 2016.
F. Giannotti, Manco, G., and Turini, F., Specifying Mining Algorithms with Iterative User-Defined Aggregates, IEEE Trans. Knowl. Data Eng., vol. 16, pp. 1232-1246, 2004.
R. Guidotti, Monreale, A., Ruggieri, S., Naretto, F., Turini, F., Pedreschi, D., and Giannotti, F., Stable and actionable explanations of black-box models through factual and counterfactual rules, Data Mining and Knowledge Discovery, 2022.
G. Tomei, Paletti, F., and Natilli, M., Stiramenti identitari. Strategie di integrazione degli strannieri nella provincia di Massa Carrara tra appartenenza etnica ed esperienza transnazionale, 2011.
G. Cornacchia and Pappalardo, L., STS-EPR: Modelling individual mobility considering the spatial, temporal, and social dimensions together, 2021.
G. Rossetti, Guidotti, R., Miliou, I., Pedreschi, D., and Giannotti, F., A supervised approach for intra-/inter-community interaction prediction in dynamic social networks, Social Network Analysis and Mining, vol. 6, p. 86, 2016.
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.
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.
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.
V. Ambriola, Giannotti, F., Pedreschi, D., and Turini, F., Symbolic Semantics and Program Reduction, IEEE Trans. Software Eng., vol. 11, pp. 784-794, 1985.
G. Rossetti, Pappalardo, L., Pedreschi, D., and Giannotti, F., Tiles: an online algorithm for community discovery in dynamic social networks, Machine Learning, vol. 106, pp. 1213–1241, 2017.
M. Nanni and Pedreschi, D., Time-focused clustering of trajectories of moving objects, J. Intell. Inf. Syst., vol. 27, pp. 267-289, 2006.
V. Morini, Pollacci, L., and Rossetti, G., Toward a Standard Approach for Echo Chamber Detection: Reddit Case Study, Applied Sciences, vol. 11, p. 5390, 2021.
S. Ceri, Palpanas, T., Valle, E. Della, Pedreschi, D., Freytag, J. - C., and Trasarti, R., Towards mega-modeling: a walk through data analysis experiences, {SIGMOD} Record, vol. 42, pp. 19–27, 2013.
A. Sirbu and Babaoglu, O., Towards operator-less data centers through data-driven, predictive, proactive autonomics, Cluster Computing, pp. 1–14, 2016.