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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.
B. Guidi, Michienzi, A., and Rossetti, G., “Towards the dynamic community discovery in decentralized online social networks”, Journal of Grid Computing, vol. 17, pp. 23–44, 2019.
R. Barbuti, Mancarella, P., Pedreschi, D., and Turini, F., “A Transformational Approach to Negation in Logic Programming”, J. Log. Program., vol. 8, pp. 201-228, 1990.
A. Rauber, Trasarti, R., and Giannotti, F., “Transparency in Algorithmic Decision Making”, ERCIM News, 2019.
M. Coscia, Rossetti, G., Giannotti, F., and Pedreschi, D., “Uncovering Hierarchical and Overlapping Communities with a Local-First Approach”, {TKDD}, vol. 9, p. 6, 2014.
V. Lorenzoni, Triulzi, I., Martinucci, I., Toncelli, L., Natilli, M., Barale, R., and Turchetti, G., “Understanding eating choices among university students: A study using data from cafeteria cashiers’ transactions”, Health Policy, vol. 125, pp. 665–673, 2021.
L. Pappalardo, Rinzivillo, S., Qu, Z., Pedreschi, D., and Giannotti, F., “{Understanding the patterns of car travel}”, The European Physical Journal Special Topics, vol. 215, pp. 61–73, 2013.
R. Guidotti, Monreale, A., Rinzivillo, S., Pedreschi, D., and Giannotti, F., “Unveiling mobility complexity through complex network analysis”, Social Network Analysis and Mining, vol. 6, p. 59, 2016.
F. Giannotti, Nanni, M., Pedreschi, D., Pinelli, F., Renso, C., Rinzivillo, S., and Trasarti, R., “Unveiling the complexity of human mobility by querying and mining massive trajectory data”, VLDB J., vol. 20, pp. 695-719, 2011.
D. Aquilino, Asirelli, P., Formuso, A., Renso, C., and Turini, F., “Using MedLan to Integrate Geographical Data”, J. Log. Program., vol. 43, pp. 3-14, 2000.
D. Aquilino, Asirelli, P., Formuso, A., Renso, C., and Turini, F., “Using Medlan to Integrate Geographical Data”, Journal of Logic Programming, pp. 3–14, 2000.
S. Ruggieri, “Using t-closeness anonymity to control for non-discrimination.”, Trans. Data Privacy, vol. 7, pp. 99–129, 2014.
G. Rossetti, Milli, L., Citraro, S., and Morini, V., “UTLDR: an agent-based framework for modeling infectious diseases and public interventions”, arXiv preprint arXiv:2011.05606, 2020.
G. Aliyev and Nanni, M., “Vehicle-Pedestrian Optimization Framework for Exposure-Aware Routing”, Mobile Networks and Applications, 2025.
D. Pedreschi and Ruggieri, S., “Verification of Logic Programs”, J. Log. Program., vol. 39, pp. 125-176, 1999.
D. Pedreschi and Ruggieri, S., “Verification of Meta-Interpreters”, J. Log. Comput., vol. 7, pp. 267-303, 1997.
D. Boncoraglio, Deri, F., Distefano, F., Fadda, D., Filippi, G., Forte, G., Licari, F., Natilli, M., Pedreschi, D., and Rinzivillo, S., “A Visual Analytics Platform to Measure Performance on University Entrance Tests (Discussion Paper)”, 2019.
S. Rinzivillo, Pedreschi, D., Nanni, M., Giannotti, F., Andrienko, N., and Andrienko, G., “Visually driven analysis of movement data by progressive clustering”, Information Visualization, vol. 7, pp. 225-239, 2008.

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