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D
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 Manco, G., “Declarative Knowledge Extraction with Interactive User-Defined Aggregates”, in FQAS, 2000, pp. 435-444.
M. Aldinucci, Ruggieri, S., and Torquati, M., “Decision tree building on multi-core using FastFlow”, Concurrency and Computation: Practice and Experience, vol. 26, pp. 800–820, 2014.
L. Corciulo, Giannotti, F., and Pedreschi, D., “Datalog with Non-Deterministic Choice Computes NDB-PTIME”, in DOOD, 1993, pp. 49-66.
F. Giannotti and Pedreschi, D., “Datalog with Non-Deterministic Choice Computers NDB-PTIME”, J. Log. Program., vol. 35, pp. 79-101, 1998.
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, Manco, G., Nanni, M., and Pedreschi, D., “Datalog++: a Basis for Active Object.Oriented Databases”, in SEBD, 1997, pp. 325-340.
L. Pappalardo and Simini, F., “Data-driven generation of spatio-temporal routines in human mobility”, Data Mining and Knowledge Discovery, 2017.
G. Amato, Giannotti, F., and Mainetto, G., “Data Sharing Analysis for a Database Programming Lanaguage via Abstract Interpretation”, in VLDB, 1993, pp. 405-415.
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. Beltram, Giannotti, F., and Pedreschi, D., “Data Science a Game-changer for Science and Innovation”. G7 Academy, 2017.
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.
R. Pellungrini, Pappalardo, L., Pratesi, F., and Monreale, A., “A Data Mining Approach to Assess Privacy Risk in Human Mobility Data”, ACM Trans. Intell. Syst. Technol., vol. 9, pp. 31:1–31:27, 2017.
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.
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.
A. Sirbu, Crane, M., and Ruskin, H. J., “Data Integration for Microarrays: Enhanced Inference for Gene Regulatory Networks”, Microarrays, vol. 4, pp. 255–269, 2015.
S. Ruggieri, “Data Anonymity Meets Non-discrimination”, in Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on, 2013.
R. Trasarti, Baglioni, M., and Renso, C., “DAMSEL: A System for Progressive Querying and Reasoning on Movement Data”, in DEXA Workshops, 2009, pp. 452-456.
R. Ortale, Ritacco, E., Pelekis, N., Trasarti, R., Costa, G., Giannotti, F., Manco, G., Renso, C., and Theodoridis, Y., “The DAEDALUS framework: progressive querying and mining of movement data”, in GIS, 2008, p. 52.
R. Ortale, Ritacco, E., Pelekisy, N., Trasarti, R., Costa, G., Giannotti, F., Manco, G., Renso, C., and Theodoridis, Y., “DAEDALUS: A knowledge discovery analysis framework for movement data”, in SEBD, 2008, pp. 191-198.
C
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.
A. Sirbu, Ruskin, H. J., and Crane, M., “Cross-platform microarray data normalisation for regulatory network inference.”, PLoS One, vol. 5, p. e13822, 2010.
F. Bonchi, Giannotti, F., Lucchese, C., Orlando, S., Perego, R., and Trasarti, R., “A constraint-based querying system for exploratory pattern discovery”, Inf. Syst., vol. 34, pp. 3-27, 2009.

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