Publications

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Conference Paper
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.
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.
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., Discrimination-aware data mining, in KDD, 2008, pp. 560-568.
C. Panigutti, Perotti, A., and Pedreschi, D., Doctor XAI: an ontology-based approach to black-box sequential data classification explanations, in Proceedings of the 2020 Conference on Fairness, Accountability, and Transparency, 2020.
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.
B. Guidi, Michienzi, A., and Rossetti, G., Dynamic community analysis in decentralized online social networks, in European Conference on Parallel Processing, 2017.
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.
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.
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.
S. Ruggieri, Enumerating Distinct Decision Trees, in International Conference on Machine Learning, 2017.
R. Guidotti and Coscia, M., On the Equivalence Between Community Discovery and Clustering, in International Conference on Smart Objects and Technologies for Social Good, 2017.
V. Voukelatou, Pappalardo, L., Gabrielli, L., and Giannotti, F., Estimating countries’ peace index through the lens of the world news as monitored by GDELT, in 2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA)2020 IEEE 7th International Conference on Data Science and Advanced Analytics (DSAA), 2020.
S. Citraro and Rossetti, G., Eva: Attribute-Aware Network Segmentation, in International Conference on Complex Networks and Their Applications, 2019.
F. Naretto, Monreale, A., and Giannotti, F., Evaluating the Privacy Exposure of Interpretable Global and Local Explainers, in Submitted at Journal of Artificial Intelligence and Law, 2023.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., ExAMiner: Optimized Level-wise Frequent Pattern Mining with Monotone Constraint, in ICDM, 2003, pp. 11-18.
F. Turini, Baglioni, M., Furletti, B., and Rinzivillo, S., Examples of Integration of Induction and Deduction in Knowledge Discovery, in Reasoning, Action and Interaction in AI Theories and Systems, 2006, pp. 307-326.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., ExAnte: Anticipated Data Reduction in Constrained Pattern Mining, in PKDD, 2003, pp. 59-70.
G. Rossetti, Exorcising the Demon: Angel, Efficient Node-Centric Community Discovery, in International Conference on Complex Networks and Their Applications, 2019.
F. Giannotti, Manco, G., Pedreschi, D., and Turini, F., Experiences with a Logic-Based Knowledge Discovery Support Environment, in AI*IA, 1999, pp. 202-213.
F. Giannotti, Manco, G., Pedreschi, D., and Turini, F., Experiences with a Logic-based knowledge discovery Support Environment, in 1999 ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery, 1999.
F. Naretto, Pellungrini, R., Fadda, D., and Rinzivillo, S., EXPHLOT: EXplainable Privacy assessment for Human LOcation Trajectories, in Discovery Science , 2023.
A. Fedele, Explain and Interpret Few-Shot Learning, in Joint Proceedings of the xAI-2023 Late-breaking Work, Demos and Doctoral Consortium co-located with the 1st World Conference on eXplainable Artificial Intelligence (xAI-2023), Lisbon, Portugal, July 26-28, 2023, 2023.

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