Publications

You are here

Export 5 results:
Author [ Title(Desc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
D
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.
D. Bacciu, Bellandi, A., Furletti, B., Grossi, V., and Romei, A., Discovering Strategic Behaviour in Multi- Agent Scenarios by Ontology-Driven Mining, in Advances in Robotics, Automation and Control, 2008.
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.
R. Trasarti, Olteanu-Raimond, A. - M., Nanni, M., Couronné, T., Furletti, B., Giannotti, F., Smoreda, Z., and Ziemlicki, C., Discovering urban and country dynamics from mobile phone data with spatial correlation patterns, Telecommunications Policy, p. -, 2014.
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.
A. Romei, Ruggieri, S., and Turini, F., Discrimination discovery in scientific project evaluation: A case study, Expert Systems with Applications, vol. 40, pp. 6064–6079, 2013.
D. Pedreschi, Ruggieri, S., and Turini, F., Discrimination-aware data mining, in KDD, 2008, pp. 560-568.
M. Baglioni, Furletti, B., and Turini, F., DrC4.5: Improving C4.5 by means of Prior Knowledge, in ACM Symposium on Applied Computing, Santa Fe, New Mexico, USA, 2005.
M. Nanni, Trasarti, R., Monreale, A., Grossi, V., and Pedreschi, D., Driving Profiles Computation and Monitoring for Car Insurance CRM, Journal ACM Transactions on Intelligent Systems and Technology (TIST), vol. 8, pp. 14:1–14:26, 2016.
A. Brogi, Renso, C., and Turini, F., Dynamic composition of parameterised logic modules, Comput. Lang., vol. 25, pp. 211-242, 1999.
A. Brogi, Renso, C., and Turini, F., Dynamic Composition of Parameterised Logic Modules, Computer Languages, pp. 211–242, 1999.
E
A. Rossi, Pappalardo, L., Cintia, P., F Iaia, M., Fernàndez, J., and Medina, D., Effective injury forecasting in soccer with GPS training data and machine learning, PloS one, vol. 13, p. e0201264, 2018.
F. Giannotti, Manco, G., Nanni, M., and Pedreschi, D., On the Effective Semantics of Nondeterministic, Nonmonotonic, Temporal Logic Databases, in CSL, 1998, pp. 58-72.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., Efficient breadth-first mining of frequent pattern with monotone constraints, Knowl. Inf. Syst., vol. 8, pp. 131-153, 2005.
K. S. Boeg, Ira Assent,, and Magnani, M., Efficient GPU-based skyline computation, in DAMON@SIGMOD 2013, 2013.
F. Giannotti, Nanni, M., and Pedreschi, D., Efficient Mining of Temporally Annotated Sequences, in SDM, 2006.
A. Baroni, Conte, A., Patrignani, M., and Ruggieri, S., Efficiently Clustering Very Large Attributed Graphs, arXiv preprint arXiv:1703.08590, 2017.
P. Contucci, Panizzi, E., Ricci-Tersenghi, F., and Sirbu, A., Egalitarianism in the rank aggregation problem: a new dimension for democracy, Quality & Quantity, pp. 1–16, 2015.
A. Sirbu, Crane, M., and Ruskin, H. J., EGIA–Evolutionary Optimisation of Gene Regulatory Networks, an Integrative Approach, in Complex Networks V, Springer International Publishing, 2014, pp. 217–229.
P. Mukala, Cerone, A., and Turini, F., An empirical verification of a-priori learning models on mailing archives in the context of online learning activities of participants in free\libre open source software (FLOSS) communities, Education and Information Technologies, vol. 22, pp. 3207–3229, 2017.
P. Cintia, Pappalardo, L., and Pedreschi, D., "Engine Matters": {A} First Large Scale Data Driven Study on Cyclists' Performance, in 13th {IEEE} International Conference on Data Mining Workshops, {ICDM} Workshops, TX, USA, December 7-10, 2013, 2013.
A. Raffaetà, Turini, F., and Renso, C., Enhancing GISs for spatio-temporal reasoning, in ACM-GIS, 2002, pp. 42-48.

Pages