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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.
F. Giannotti, Trasarti, R., Bontcheva, K., and Grossi, V., SoBigData: Social Mining & Big Data Ecosystem, in Companion of the The Web Conference 2018 on The Web Conference 2018, 2018.
M. Coscia, Giannotti, F., and Pensa, R. G., Social Network Analysis as Knowledge Discovery Process: A Case Study on Digital Bibliography, in ASONAM, 2009, pp. 279-283.
M. Coscia, Giannotti, F., and Pensa, R. G., Social Network Analysis as Knowledge Discovery Process: A Case Study on Digital Bibliography, in ASONAM, 2009, pp. 279-283.
R. Guidotti, Sassi, A., Berlingerio, M., Pascale, A., and Ghaddar, B., Social or green? A data-driven approach for more enjoyable carpooling, in Intelligent Transportation Systems (ITSC), 2015 IEEE 18th International Conference on, 2015.
M. Setzu and Atzori, M., SPARQL Queries over Source Code, in 2016 IEEE Tenth International Conference on Semantic Computing (ICSC), 2016.
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. Wachowicz and Renso, C., Spatio and Spatio-temporal Reasoning and Decision Support Tools, in Entry at Encyclopedia of Social Network Analysis and Mining, Springer., 2013.
V. Cozza, Messina, A., Montesi, D., Arietta, L., and Magnani, M., Spatio temporal keyword-queries in Social Networs, 2013.
S. Kisilevich, Mansmann, F., Nanni, M., and Rinzivillo, S., Spatio-temporal clustering, in Data Mining and Knowledge Discovery Handbook, 2010, pp. 855-874.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., Spatio-Temporal Data, Spatio-Temporal Databases: Flexible Querying and Reasoning, p. 75, 2013.
M. Nanni, Kuijpers, B., Körner, C., May, M., and Pedreschi, D., Spatiotemporal Data Mining, in Mobility, Data Mining and Privacy, 2008, pp. 267-296.
M. E. Carboni, Deo, A. D., Giannotti, F., and Masserotti, M. V., Spatio-Temporal Reasoning with LDLT: First Steps Towards a Deductive System for Geographical Applications, in DDLP, 1996, pp. 135-151.
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: A Case Study, in PKDD, 2001, pp. 128-139.
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 and Ruggieri, S., On The Stability of Interpretable Models, in 2019 International Joint Conference on Neural Networks (IJCNN), 2019.
A. Sirbu, Ruskin, H. J., and Crane, M., Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role, in Evolutionary Algorithms, InTech, 2011.
G. Amato, Giannotti, F., and Mainetto, G., Static Analysis of Transactions: an Experiment of Abstract Interpretation Usage, in FMLDO, 1993, pp. 19-29.
G. Amato, Giannotti, F., and Mainetto, G., Static Analysis of Transactions for Conservative Multigranularity Locking, in DBPL, 1997, pp. 413-430.
R. Ong, Nanni, M., Renso, C., Wachowicz, M., and Pedreschi, D., A Study on Parameter Estimation for a Mining Flock Algorithm , in Mining Complex Patterns Workshop, ECML PKDD 2013, 2013.
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.
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, 2019.

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