Publications

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Conference Paper
L. Pollacci, Sirbu, A., Giannotti, F., Pedreschi, D., Lucchese, C., and Muntean, C. Ioana, Sentiment Spreading: An Epidemic Model for Lexicon-Based Sentiment Analysis on Twitter, in Conference of the Italian Association for Artificial Intelligence, 2017.
A. Baroni and Ruggieri, S., Segregation Discovery in a Social Network of Companies, in International Symposium on Intelligent Data Analysis, 2015.
G. Rossetti, Berlingerio, M., and Giannotti, F., Scalable Link Prediction on Multidimensional Networks, in ICDM Workshops, Vancouver, 2011, pp. 979-986.
F. Bonchi, Giannotti, F., and Pedreschi, D., A Relational Query Primitive for Constraint-Based Pattern Mining, in Constraint-Based Mining and Inductive Databases, 2004, pp. 14-37.
R. Guidotti and Gabrielli, L., Recognizing Residents and Tourists with Retail Data Using Shopping Profiles, in International Conference on Smart Objects and Technologies for Social Good, 2017.
C. Bertazzoni and Giannotti, F., RASP: A Resource Allocator for Software Projects, in IEA/AIE (Vol. 2), 1990, pp. 628-637.
M. E. Carboni, Deo, A. D., Giannotti, F., and Masserotti, M. V., Ragionamento spazio-temporale con LDLT: primi esperimenti verso un sistema deduttivo per applicazioni geografiche, in SEBD, 1996, pp. 73-90.
F. Giannotti and Manco, G., Querying Inductive Databases via Logic-Based User-Defined Aggregates, in PKDD, 1999, pp. 125-135.
F. Giannotti and Manco, G., Querying inductive Databases via Logic-Based user-defined aggregates, in APPIA-GULP-PRODE, 1999, pp. 605-620.
M. Nanni and Trasarti, R., Querying and mining trajectories with gaps: a multi-path reconstruction approach (Extended Abstract), in SEBD, 2010, pp. 126-133.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., Query Answering in Nondeterministic, Nonmonotonic Logic Databases, in FQAS, 1998, pp. 175-187.
L. Milli, Monreale, A., Rossetti, G., Giannotti, F., Pedreschi, D., and Sebastiani, F., Quantification Trees, in 2013 IEEE 13th International Conference on Data Mining, Dallas, TX, USA, December 7-10, 2013, 2013, pp. 528–536.
L. Milli, Monreale, A., Rossetti, G., Pedreschi, D., Giannotti, F., and Sebastiani, F., Quantification in Social Networks, in International Conference on Data Science and Advanced Analytics (IEEE DSAA'2015), Paris, France, 2015.
A. Raffaetà, Renso, C., and Turini, F., Qualitative Spatial Reasoning in a Logical Framework, in AI*IA, 2003, pp. 78-90.
A. Raffaetà, Renso, C., and Turini, F., Qualitative Reasoning in a Spatio-Temporal Language, in SEBD, 2002, pp. 105-118.
F. Bonchi and Giannotti, F., Pushing Constraints to Detect Local Patterns, in Local Pattern Detection, 2004, pp. 1-19.
B. Furletti, Bellandi, A., Romei, A., and Grossi, V., PUSHING CONSTRAINTS IN ASSOCIATION RULE MINING: AN ONTOLOGY-BASED APPROACH , in IADIS International Conference WWW/Internet 2007, 2007.
S. Rinzivillo, Gabrielli, L., Nanni, M., Pappalardo, L., Pedreschi, D., and Giannotti, F., The purpose of motion: Learning activities from Individual Mobility Networks, in International Conference on Data Science and Advanced Analytics, {DSAA} 2014, Shanghai, China, October 30 - November 1, 2014, 2014.
P. Mascellani and Pedreschi, D., Proving termination of Prolog programs, in GULP-PRODE (1), 1994, pp. 46-61.
K. R. Apt and Pedreschi, D., Proving Termination of General Prolog Programs, in TACS, 1991, pp. 265-289.
D. Pedreschi, A Proof Method for Runtime Properties of Prolog Programs, in ICLP, 1994, pp. 584-598.
B. Bertolino, Mancarella, P., Meo, L., Nini, L., Pedreschi, D., and Turini, F., A Progress Report on the LML Project, in FGCS, 1988, pp. 675-684.
P. Mukala, Cerone, A., and Turini, F., Process mining event logs from FLOSS data: state of the art and perspectives, in International Conference on Software Engineering and Formal Methods, 2014.
F. D. C. Albuquerque, Casanova, M. A., de Carvalho, M. T. M., de Macêdo, J. A. F., and Renso, C., A Proactive Ap- plication to Monitor Truck Fleets, in Mobile Data Management Conference, 2013, 2013.
A. Marrella, Monreale, A., Kloepper, B., and Krueger, M. W., Privacy-Preserving Outsourcing of Pattern Mining of Event-Log Data-A Use-Case from Process Industry, in Cloud Computing Technology and Science (CloudCom), 2016 IEEE International Conference on, 2016.

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