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M. Nanni and Pedreschi, D., Time-focused clustering of trajectories of moving objects, J. Intell. Inf. Syst., vol. 27, pp. 267-289, 2006.
M. Berlingerio, Bonchi, F., Giannotti, F., and Turini, F., Time-Annotated Sequences for Medical Data Mining, in ICDM Workshops, 2007, pp. 133-138.
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.
D. Pennacchioli, Rossetti, G., Pappalardo, L., Pedreschi, D., Giannotti, F., and Coscia, M., The Three Dimensions of Social Prominence, in Social Informatics - 5th International Conference, SocInfo 2013, Kyoto, Japan, November 25-27, 2013, Proceedings, 2013.
R. Guidotti, Trasarti, R., Nanni, M., Giannotti, F., and Pedreschi, D., There's A Path For Everyone: A Data-Driven Personal Model Reproducing Mobility Agendas, in 4th IEEE International Conference on Data Science and Advanced Analytics (DSAA 2017), Tokyo, 2017.
A. Brogi, Mancarella, P., Pedreschi, D., and Turini, F., Theory Construction in Computational Logic, in ICLP Workshop on Construction of Logic Programs, 1991, pp. 241-250.
A. Raffaetà and Renso, C., Temporal Reasoning in Geographical Information Systems, in DEXA Workshop, 2000, pp. 899-905.
M. Berlingerio, Pinelli, F., Nanni, M., and Giannotti, F., Temporal mining for interactive workflow data analysis, in KDD, 2009, pp. 109-118.
M. Berlingerio, Giannotti, F., Nanni, M., and Pinelli, F., Temporal analysis of process logs: a case study, in SEBD, 2008, pp. 430-437.
F. Giannotti and Hermenegildo, M. V., A Technique for Recursive Invariance Detection and Selective Program Specification, in PLILP, 1991, pp. 323-334.
M. Wachowicz, Ong, R., and Renso, C., Tailoring Moving Patterns to Contexts, in AGILE Conference, Leuven, Belgium, 2013, 2013.
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F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., Synthetic generation of cellular network positioning data, in GIS, 2005, pp. 12-20.
F. Giannotti, Mazzoni, A., Puntoni, S., and Renso, C., Synthetic generation of cellular network positioning data, in GIS, 2005, pp. 12-20.
V. Ambriola, Giannotti, F., Pedreschi, D., and Turini, F., Symbolic Semantics and Program Reduction, IEEE Trans. Software Eng., vol. 11, pp. 784-794, 1985.
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. Grossi, Romei, A., and Turini, F., Survey on using constraints in data mining, Data Mining and Knowledge Discovery, vol. 31, pp. 424–464, 2017.
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.
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. 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. Cornacchia and Pappalardo, L., STS-EPR: Modelling individual mobility considering the spatial, temporal, and social dimensions together, 2021.
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. Amato, Giannotti, F., and Mainetto, G., Static Analysis of Transactions for Conservative Multigranularity Locking, in DBPL, 1997, pp. 413-430.
G. Amato, Giannotti, F., and Mainetto, G., Static Analysis of Transactions: an Experiment of Abstract Interpretation Usage, in FMLDO, 1993, pp. 19-29.
A. Sirbu, Ruskin, H. J., and Crane, M., Stages of Gene Regulatory Network Inference: the Evolutionary Algorithm Role, in Evolutionary Algorithms, InTech, 2011.
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.

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