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Conference Paper
G. Amato, Giannotti, F., and Mainetto, G., “Conservative Multigranularity Locking for an Obiect-Oriented Persistent Language via Abstract Interpretation”, in SEBD, 1994, pp. 329-349.
P. Asirelli, Renso, C., and Turini, F., “The Constraint Operator of MedLan: Its Efficient Implementation and Use”, in IICIS, 1998, pp. 41-55.
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.
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. Trasarti, Baglioni, M., and Renso, C., “DAMSEL: A System for Progressive Querying and Reasoning on Movement Data”, in DEXA Workshops, 2009, pp. 452-456.
S. Ruggieri, “Data Anonymity Meets Non-discrimination”, in Data Mining Workshops (ICDMW), 2013 IEEE 13th International Conference on, 2013.
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.
G. Amato, Giannotti, F., and Mainetto, G., “Data Sharing Analysis for a Database Programming Lanaguage via Abstract Interpretation”, in VLDB, 1993, pp. 405-415.
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.
L. Corciulo, Giannotti, F., and Pedreschi, D., “Datalog with Non-Deterministic Choice Computes NDB-PTIME”, in DOOD, 1993, pp. 49-66.
F. Giannotti and Manco, G., “Declarative Knowledge Extraction with Interactive User-Defined Aggregates”, in FQAS, 2000, pp. 435-444.
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.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., “Deductive and Inductive Reasoning on Spatio-Temporal Data”, in INAP/WLP, 2004, pp. 98-115.
M. Nanni, Raffaetà, A., Renso, C., and Turini, F., “Deductive and Inductive Reasoning on Trajectories”, in SEBD, 2004, pp. 98-105.
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 The 18th {ACM} {SIGKDD} International Conference on Knowledge Discovery and Data Mining, {KDD} '12, Beijing, China, August 12-16, 2012, 2012.
M. Coscia, Rossetti, G., Giannotti, F., and Pedreschi, D., “DEMON: a Local-First Discovery Method for Overlapping Communities”, in KDD 2012, 2012.
B. Furletti, Gabrielli, L., Trasarti, R., Smoreda, Z., Vanhoof, M., and Ziemlicki, C., “Detecting and understanding big events in big cities”, in NetMob, Boston, 2015.
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.
J. Kim, Sirbu, A., Giannotti, F., and Gabrielli, L., “Digital Footprints of International Migration on Twitter”, in International Symposium on Intelligent Data Analysis, 2020.

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