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C. Bessiere, De Raedt, L., Kotthoff, L., Nijssen, S., O'Sullivan, B., and Pedreschi, D., Data Mining and Constraint Programming - Foundations of a Cross-Disciplinary Approach.. 2016.
V. Grossi, Pedreschi, D., and Turini, F., Data Mining and Constraints: An Overview, in Data Mining and Constraint Programming, Springer International Publishing, 2016, pp. 25–48.
F. Bonchi, Giannotti, F., Manco, G., Renso, C., Nanni, M., Pedreschi, D., and Ruggieri, S., Data Mining for Intelligent Web Caching, in ITCC, 2001, pp. 599-603.
F. Bonchi, Giannotti, F., Manco, G., Renso, C., Nanni, M., Pedreschi, D., and Ruggieri, S., Data Mining for Intelligent Web Caching, in ITCC, 2001, pp. 599-603.
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, Manco, G., Nanni, M., and Pedreschi, D., Datalog++: a Basis for Active Object.Oriented Databases, in SEBD, 1997, pp. 325-340.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., Datalog++: A Basis for Active Object-Oriented Databases, in DOOD, 1997, pp. 283-301.
F. Giannotti and Pedreschi, D., Datalog with Non-Deterministic Choice Computers NDB-PTIME, J. Log. Program., vol. 35, pp. 79-101, 1998.
L. Corciulo, Giannotti, F., and Pedreschi, D., Datalog with Non-Deterministic Choice Computes NDB-PTIME, in DOOD, 1993, pp. 49-66.
M. E. Carboni, Giannotti, F., Foddai, V., and Pedreschi, D., Declarative Reconstruction of Updates in Logic Databases: A Compilative Approach, in SEBD, 1995, pp. 3-13.
M. E. Carboni, Foddai, V., Giannotti, F., and Pedreschi, D., Declarative Reconstruction of Updates in Logic Databases: a Compilative Approach, in GULP-PRODE, 1995, pp. 169-182.
F. Giannotti and Pedreschi, D., Declarative Semantics for Pruning Operators in Logic Programming, in LPNMR, 1990, pp. 27-37.
P. Mascellani and Pedreschi, D., The Declarative Side of Magic, in Computational Logic: Logic Programming and Beyond, 2002, pp. 83-108.
F. Giannotti, Manco, G., and Pedreschi, D., A Deductive Data Model for Representing and Querying Semistructured Data, in APPIA-GULP-PRODE, 1997, pp. 129-140.
M. Coscia, Rossetti, G., Giannotti, F., and Pedreschi, D., DEMON: a Local-First Discovery Method for Overlapping Communities, in KDD 2012, 2012.
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.
L. Milli, Rossetti, G., Pedreschi, D., and Giannotti, F., Diffusive Phenomena in Dynamic Networks: a data-driven study, in International Conference on Complex Networks CompleNet, Boston March 5-8 2018, 2018.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., Discovering Eras in Evolving Social Networks (Extended Abstract), in SEBD, 2010, pp. 78-85.
L. Gabrielli, Fadda, D., Rossetti, G., Nanni, M., Piccinini, L., Pedreschi, D., Giannotti, F., and Lattarulo, P., Discovering Mobility Functional Areas: A Mobility Data Analysis Approach, in International Workshop on Complex Networks, 2018.
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.
V. Bacarella, Giannotti, F., Nanni, M., and Pedreschi, D., Discovery of ads web hosts through traffic data analysis, in DMKD, 2004, pp. 76-81.
D. Pedreschi, Ruggieri, S., and Turini, F., The discovery of discrimination, in Discrimination and privacy in the information society, Springer, 2013, pp. 91–108.
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.
D. Pedreschi, Ruggieri, S., and Turini, F., Discrimination-aware data mining, in KDD, 2008, pp. 560-568.

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