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C
G. Cornacchia and Pappalardo, L., STS-EPR: Modelling individual mobility considering the spatial, temporal, and social dimensions together, 2021.
G. Cornacchia, Rossetti, G., and Pappalardo, L., Modelling Human Mobility considering Spatial, Temporal and Social Dimensions, arXiv preprint arXiv:2007.02371, 2020.
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 Pedreschi, D., A classification for community discovery methods in complex networks, Statistical Analysis and Data Mining, vol. 4, pp. 512-546, 2011.
M. Coscia, Rinzivillo, S., Pedreschi, D., and Giannotti, F., Optimal Spatial Resolution for the Analysis of Human Mobility, IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining. Instanbul, Turkey, 2012.
M. Coscia, Rossetti, G., Giannotti, F., and Pedreschi, D., DEMON: a Local-First Discovery Method for Overlapping Communities, in KDD 2012, 2012.
M. Coscia, Pennacchioli, D., and Giannotti, F., Product assortment and customer mobility, EPJ Data Science, vol. 4, pp. 1–18, 2015.
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. Coscia, Rossetti, G., Giannotti, F., and Pedreschi, D., Uncovering Hierarchical and Overlapping Communities with a Local-First Approach, {TKDD}, vol. 9, p. 6, 2014.
M. Coscia, Rossetti, G., Giannotti, F., and Pedreschi, D., DEMON: a local-first discovery method for overlapping communities, in The 18th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining, {KDD} '12, Beijing, China, August 12-16, 2012, 2012.
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, Rossetti, G., Pennacchioli, D., Ceccarelli, D., and Giannotti, F., You Know Because I Know”: a Multidimensional Network Approach to Human Resources Problem, in ASONAM 2013, 2013.
V. Cozza, Messina, A., Montesi, D., Arietta, L., and Magnani, M., Spatio temporal keyword-queries in Social Networs, 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.
E
P. Eirinakis, Ruggieri, S., Subramani, K., and Wojciechowski, P., On quantified linear implications, Annals of Mathematics and Artificial Intelligence, vol. 71, pp. 301–325, 2014.
F
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.
A. Failla, Citraro, S., and Rossetti, G., Attributed Stream Hypergraphs: temporal modeling of node-attributed high-order interactions, Applied Network Science, vol. 8, pp. 1–19, 2023.
A. Failla, Citraro, S., and Rossetti, G., Attributed stream-hypernetwork analysis: homophilic behaviors in pairwise and group political discussions on reddit, in International Conference on Complex Networks and Their Applications, 2022.
A. Failla, Mazzoni, F., and Citraro, S., Attribute-aware Community Events in Feature-rich Dynamic Networks, in Complex Networks and Their Applications XI: Proceedings of The Eleventh International Conference on Complex Networks and Their Applications: COMPLEX NETWORKS 2022—Book of Abstracts, 2022.
M. Fayzullin, Nanni, M., Pedreschi, D., and Subrahmanian, V. S., Foundations of distributed interaction systems, Ann. Math. Artif. Intell., vol. 28, pp. 127-168, 2000.
A. Fedele, Explain and Interpret Few-Shot Learning, in Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lisbon, Portugal, July 26-28, 2023, 2023.
A. Fedele, Guidotti, R., and Pedreschi, D., Explaining Siamese Networks in Few-Shot Learning for Audio Data, in Discovery Science - 25th International Conference, DS 2022, Montpellier, France, October 10-12, 2022, Proceedings, 2022.

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