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Journal Article
L. Pappalardo, Rossi, A., Natilli, M., and Cintia, P., Explaining the difference between men’s and women’s football, PLOS ONE, vol. 16, p. e0255407, 2021.
F. Bodria, Rinzivillo, S., Fadda, D., Guidotti, R., Giannotti, F., and Pedreschi, D., Explaining Black Box with visual exploration of Latent Space, EuroVis–Short Papers, 2022.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., Exante: A Preprocessing Method for Frequent-Pattern Mining, IEEE Intelligent Systems, vol. 20, pp. 25-31, 2005.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., Evolving networks: Eras and turning points, Intell. Data Anal., vol. 17, pp. 27–48, 2013.
R. Cazabet, Boudebza, S., and Rossetti, G., Evaluating community detection algorithms for progressively evolving graphs, arXiv preprint arXiv:2007.08635, 2020.
N. Forgó, Hänold, S., van den Hoven, J., Krügel, T., Lishchuk, I., Mahieu, R., Monreale, A., Pedreschi, D., Pratesi, F., and van Putten, D., An ethico-legal framework for social data science, 2020.
F. Lillo and Ruggieri, S., Estimating the Total Volume of Queries to a Search Engine, IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2021.
A. Rossi, Pedreschi, D., Clifton, D. A., and Morelli, D., Error Estimation of Ultra-Short Heart Rate Variability Parameters: Effect of Missing Data Caused by Motion Artifacts, Sensors, vol. 20, p. 7122, 2020.
P. Mukala, Cerone, A., and Turini, F., An empirical verification of a-priori learning models on mailing archives in the context of online learning activities of participants in free\libre open source software (FLOSS) communities, Education and Information Technologies, vol. 22, pp. 3207–3229, 2017.
P. Contucci, Panizzi, E., Ricci-Tersenghi, F., and Sirbu, A., Egalitarianism in the rank aggregation problem: a new dimension for democracy, Quality & Quantity, pp. 1–16, 2015.
A. Baroni, Conte, A., Patrignani, M., and Ruggieri, S., Efficiently Clustering Very Large Attributed Graphs, arXiv preprint arXiv:1703.08590, 2017.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., Efficient breadth-first mining of frequent pattern with monotone constraints, Knowl. Inf. Syst., vol. 8, pp. 131-153, 2005.
A. Rossi, Pappalardo, L., Cintia, P., F Iaia, M., Fernàndez, J., and Medina, D., Effective injury forecasting in soccer with GPS training data and machine learning, PloS one, vol. 13, p. e0201264, 2018.
Conference Paper
S. Rinzivillo and Turini, F., Extracting spatial association rules from spatial transactions, in ACM GIS, 2005, pp. 79-86.
B. Furletti, Fornasari, F., and Montanari, C., AN EXTENSIBLE AND INTERACTIVE SOFTWARE AGENT FOR MOBILE DEVICES BASED ON GPS DATA, in IADIS International Conference Applied Computing, 2008.
L. Corciulo, Giannotti, F., Pedreschi, D., and Zaniolo, C., Expressive Power of Non-Deterministic Operators for Logic-based Languages, in Workshop on Deductive Databases and Logic Programming, 1994, pp. 27-40.
M. Natilli, Monreale, A., Guidotti, R., and Pappalardo, L., Exploring Students Eating Habits Through Individual Profiling and Clustering Analysis, in ECML PKDD 2018 Workshops, 2018.
R. Trasarti, Rinzivillo, S., Pinelli, F., Nanni, M., Monreale, A., Renso, C., Pedreschi, D., and Giannotti, F., Exploring Real Mobility Data with M-Atlas, in ECML/PKDD (3), 2010, pp. 624-627.
R. Guidotti, Soldani, J., Neri, D., and Brogi, A., Explaining successful docker images using pattern mining analysis, in Federation of International Conferences on Software Technologies: Applications and Foundations, 2018.
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.
O. Lampridis, Guidotti, R., and Ruggieri, S., Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars, in Discovery Science, Cham, 2020.
C. Panigutti, Guidotti, R., Monreale, A., and Pedreschi, D., Explaining multi-label black-box classifiers for health applications, in International Workshop on Health Intelligence, 2019.
L. Corbucci, Guidotti, R., and Monreale, A., Explaining Black-Boxes in Federated Learning, in Explainable Artificial Intelligence, Cham, 2023.

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