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Journal Article
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.
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.
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.
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., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, Journal of Intelligent Information Systems, pp. 1–13, 2019.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., Classes of Terminating Logic Programs, CoRR, vol. cs.LO/0106, 2001.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., Classes of terminating logic programs, TPLP, vol. 2, pp. 369-418, 2002.
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.
K. R. Apt, Gabbrielli, M., and Pedreschi, D., A Closer Look at Declarative Interpretations, J. Log. Program., vol. 28, pp. 147-180, 1996.
P. Mancarella, Martini, S., and Pedreschi, D., Complete Logic Programs with Domain-Closure Axiom, J. Log. Program., vol. 5, pp. 263-276, 1988.
A. Monreale, Trasarti, R., Pedreschi, D., Renso, C., and Bogorny, V., C-safety: a framework for the anonymization of semantic trajectories, Transactions on Data Privacy, vol. 4, pp. 73-101, 2011.
D. Janssens, Giannotti, F., Nanni, M., Pedreschi, D., and Rinzivillo, S., Data Science for Simulating the Era of Electric Vehicles, KI - Künstliche Intelligenz, 2012.
F. Giannotti and Pedreschi, D., Datalog with Non-Deterministic Choice Computers NDB-PTIME, J. Log. Program., vol. 35, pp. 79-101, 1998.
R. Guidotti, Gabrielli, L., Monreale, A., Pedreschi, D., and Giannotti, F., Discovering temporal regularities in retail customers’ shopping behavior, EPJ Data Science, vol. 7, p. 6, 2018.
S. Rinzivillo, Mainardi, S., Pezzoni, F., Coscia, M., Giannotti, F., and Pedreschi, D., Discovering the Geographical Borders of Human Mobility, KI - Künstliche Intelligenz, 2012.
S. Hajian, Domingo-Ferrer, J., Monreale, A., Pedreschi, D., and Giannotti, F., Discrimination- and privacy-aware patterns, Data Min. Knowl. Discov., vol. 29, pp. 1733–1782, 2015.
M. Nanni, Trasarti, R., Monreale, A., Grossi, V., and Pedreschi, D., Driving Profiles Computation and Monitoring for Car Insurance CRM, Journal ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, pp. 14:1–14:26, 2016.
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.
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.
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.
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.
R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., Factual and Counterfactual Explanations for Black Box Decision Making, IEEE Intelligent Systems, 2019.
G. Rossetti, Milli, L., Giannotti, F., and Pedreschi, D., Forecasting success via early adoptions analysis: A data-driven study, PloS one, vol. 12, p. e0189096, 2017.

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