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Journal Article
G. Rossetti, “ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks”, Applied Network Science, vol. 5, pp. 1–23, 2020.
M. Atzori, Bonchi, F., Giannotti, F., and Pedreschi, D., “Anonymity and data mining”, Comput. Syst. Sci. Eng., vol. 20, 2005.
M. Atzori, Bonchi, F., Giannotti, F., and Pedreschi, D., “Anonymity preserving pattern discovery”, VLDB J., vol. 17, pp. 703-727, 2008.
A. Monreale, Pedreschi, D., Pensa, R. G., and Pinelli, F., “Anonymity preserving sequential pattern mining”, Artif. Intell. Law, vol. 22, pp. 141–173, 2014.
A. Raffaetà, Ceccarelli, T., Centeno, D., Giannotti, F., Massolo, A., Parent, C., Renso, C., Spaccapietra, S., and Turini, F., “An Application of Advanced Spatio-Temporal Formalisms to Behavioural Ecology”, GeoInformatica, vol. 12, pp. 37-72, 2008.
T. Ceccarelli, Centeno, D., Giannotti, F., Massolo, A., Parent, C., Raffaetà, A., Renso, C., Spaccapietra, S., and Turini, F., “An Application of Advanced Spatio-Temporal Formalisms to Behavioural Ecology”, 2008.
D. Aquilino, Asirelli, P., Renso, C., and Turini, F., “Applying Restriction Constraint to Deductive Databases”, Annals of Mathematics and Artificial Intelligence, pp. 3–25, 1997.
D. Aquilino, Asirelli, P., Renso, C., and Turini, F., “Applying Restriction Constraints to Deductive Databases”, Ann. Math. Artif. Intell., vol. 19, pp. 3-25, 1997.
A. S. Furtado, Fileto, R., and Renso, C., “Assessing the Attractiveness of Places with Movement Data ”, Journal of Information and Data Management, vol. 4, 2013.
R. Guidotti and Ruggieri, S., “Assessing the Stability of Interpretable Models”, arXiv preprint arXiv:1810.09352, 2018.
C. Panigutti, Tizzoni, M., Bajardi, P., Smoreda, Z., and Colizza, V., “Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models”, Royal Society open science, vol. 4, p. 160950, 2017.
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.
B. Dong, Wang, H. Wendy, Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., “Authenticated Outlier Mining for Outsourced Databases”, IEEE Transactions on Dependable and Secure Computing, 2017.
B. Dong, Wang, H., Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., “Authenticated Outlier Mining for Outsourced Databases”, IEEE Transactions on Dependable and Secure Computing, vol. 17, pp. 222 - 235, 2020.
M. Becker, Caminiti, S., Fiorella, D., Francis, L., Gravino, P., Haklay, M. Muki, Hotho, A., Loreto, V., Mueller, J., Ricchiuti, F., Servedio, V. D. P., Sirbu, A., and Tria, F., “Awareness and learning in participatory noise sensing.”, PLoS One, vol. 8, p. e81638, 2013.
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., “Benchmarking and Survey of Explanation Methods for Black Box Models”, CoRR, vol. abs/2102.13076, 2021.
E. Ntoutsi, Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. - E., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., and others, “Bias in data-driven artificial intelligence systems—An introductory survey”, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 10, p. e1356, 2020.
A. Balliu, Olivetti, D., Babaoglu, O., Marzolla, M., and Sirbu, A., “A Big Data Analyzer for Large Trace Logs”, Computing, 2015.
S. Bergamaschi, Carlini, E., Ceci, M., Furletti, B., Giannotti, F., Malerba, D., Mezzanzanica, M., Monreale, A., Pasi, G., Pedreschi, D., Perego, R., and Ruggieri, S., “Big Data Research in Italy: A Perspective”, Engineering, vol. 2, p. 163, 2016.
D. Pedreschi and Ruggieri, S., “Bounded Nondeterminism of Logic Programs”, Ann. Math. Artif. Intell., vol. 42, pp. 313-343, 2004.
B. Qureshi, Kamiran, F., Karim, A., and Ruggieri, S., “Causal Discrimination Discovery Through Propensity Score Analysis”, arXiv preprint arXiv:1608.03735, 2016.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., “Causal inference for social discrimination reasoning”, vol. 54, pp. 425 - 437, 2020.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., “Causal inference for social discrimination reasoning”, Journal of Intelligent Information Systems, pp. 1–13, 2019.
G. Rossetti, Milli, L., and Cazabet, R., “CDLIB: a python library to extract, compare and evaluate communities from complex networks”, Applied Network Science, vol. 4, p. 52, 2019.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., “Classes of Terminating Logic Programs”, CoRR, vol. cs.LO/0106, 2001.

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