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G. Amato, Giannotti, F., and Mainetto, G., “Data Sharing Analysis for a Database Programming Lanaguage via Abstract Interpretation”, in VLDB, 1993, pp. 405-415.
L. Pappalardo and Simini, F., “Data-driven generation of spatio-temporal routines in human mobility”, Data Mining and Knowledge Discovery, 2017.
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. 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.
F. Giannotti and Manco, G., “Declarative Knowledge Extraction with Interactive User-Defined Aggregates”, in FQAS, 2000, pp. 435-444.
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.
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.
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.
S. Bruestle, Pappalardo, L., and Guidotti, R., “Defining Geographic Markets from Probabilistic Clusters: A Machine Learning Algorithm Applied to Supermarket Scanner Data”, Available at SSRN 3452058, 2019.
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.
C. R. Daniel Ornellana, “Developing a Spatial Knowledge Representation for Pedestrian Interactions”, 2009.
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.
G. Tomei and Natilli, M., Dinamiche di impoverimento. Meccanismi, traiettorie ed effetti in un contesto locale. Carocci Editore, 2011.
B. Furletti, Trasarti, R., Cintia, P., and Gabrielli, L., “Discovering and Understanding City Events with Big Data: The Case of Rome”, Information, vol. 8, p. 74, 2017.
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.

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