Publications

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Journal Article
S. Ruggieri, Introduction to the special issue on Artificial Intelligence for Society and Economy, Intelligenza Artificiale, vol. 9, pp. 23–23, 2015.
S. Mascetti, Ricci, A., and Ruggieri, S., Introduction to special issue on computational methods for enforcing privacy and fairness in the knowledge society, Artificial Intelligence and Law, vol. 22, pp. 109–111, 2014.
P. Mancarella, Raffaetà, A., Renso, C., and Turini, F., Integrating Knowledge Representation and Reasoning in Geographical, 2004.
P. Mancarella, Raffaetà, A., Renso, C., and Turini, F., Integrating knowledge representation and reasoning in Geographical Information Systems, International Journal of Geographical Information Science, vol. 18, pp. 417-447, 2004.
A. Sirbu, Ruskin, H. J., and Crane, M., Integrating heterogeneous gene expression data for gene regulatory network modelling., Theory Biosci, vol. 131, pp. 95-102, 2012.
C. Bessiere, De Raedt, L., Guns, T., Kotthoff, L., Nanni, M., Nijssen, S., O'Sullivan, B., Paparrizou, A., Pedreschi, D., and Simonis, H., The Inductive Constraint Programming Loop, IEEE Intelligent Systems, 2017.
M. Nanni, Nijssen, S., O'Sullivan, B., Paparrizou, A., Pedreschi, D., and Simonis, H., The Inductive Constraint Programming Loop, Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, vol. 10101, p. 303, 2017.
B. Furletti, Turini, F., Bellandi, A., Baglioni, M., and Pratesi, C., Improving the Business Plan Evaluation Process: the Role of Intangibles, Quality Technology & Quantitative Management, vol. 7, 2010.
A. Brogi, Chiarelli, A., Mancarella, P., Mazzotta, V., Pedreschi, D., Renso, C., and Turini, F., Implementations of Program Composition Operations, pp. 292–307, 1994.
M. Nanni, Kotthoff, L., Guidotti, R., O'Sullivan, B., and Pedreschi, D., ICON Loop Carpooling Show Case, Data Mining and Constraint Programming: Foundations of a Cross-Disciplinary Approach, vol. 10101, p. 310, 2017.
L. Candela, Manghi, P., Giannotti, F., Grossi, V., and Trasarti, R., HyWare: a HYbrid Workflow lAnguage for Research E-infrastructures, D-Lib Magazine, vol. 23, 2017.
A. Sirbu, Andrienko, G., Andrienko, N., Boldrini, C., Conti, M., Giannotti, F., Guidotti, R., Bertoli, S., Kim, J., Muntean, C. Ioana, and others, Human migration: the big data perspective, International Journal of Data Science and Analytics, pp. 1–20, 2020.
C. Renso, Baglioni, M., de Macêdo, J. Antônio F., Trasarti, R., and Wachowicz, M., How you move reveals who you are: understanding human behavior by analyzing trajectory data, Knowl. Inf. Syst., vol. 37, pp. 331–362, 2013.
G. Rossetti, Pappalardo, L., Kikas, R., Pedreschi, D., Giannotti, F., and Dumas, M., Homophilic network decomposition: a community-centric analysis of online social services, Social Network Analysis and Mining, vol. 6, p. 103, 2016.
R. Prieto Curiel, Pappalardo, L., Gabrielli, L., and Bishop, S. Richard, Gravity and scaling laws of city to city migration, PLOS ONE, vol. 13, pp. 1-19, 2018.
F. Giannotti and Latella, D., Gate Splitting in LOTOS Specifications Using Abstract Interpretation, Sci. Comput. Program., vol. 23, pp. 127-149, 1994.
I. Martinucci, Natilli, M., Lorenzoni, V., Pappalardo, L., Monreale, A., Turchetti, G., Pedreschi, D., Marchi, S., Barale, R., and de Bortoli, N., Gastroesophageal reflux symptoms among Italian university students: epidemiology and dietary correlates using automatically recorded transactions, BMC gastroenterology, vol. 18, p. 116, 2018.
M. Fayzullin, Nanni, M., Pedreschi, D., and Subrahmanian, V. S., Foundations of distributed interaction systems, Ann. Math. Artif. Intell., vol. 28, pp. 127-168, 2000.
G. Rossetti, Milli, L., Giannotti, F., and Pedreschi, D., Forecasting success via early adoptions analysis: A data-driven study, PloS one, vol. 12, p. e0189096, 2017.
R. Guidotti, Monreale, A., Giannotti, F., Pedreschi, D., Ruggieri, S., and Turini, F., Factual and Counterfactual Explanations for Black Box Decision Making, IEEE Intelligent Systems, 2019.
F. Bonchi, Giannotti, F., Mazzanti, A., and Pedreschi, D., Exante: A Preprocessing Method for Frequent-Pattern Mining, IEEE Intelligent Systems, vol. 20, pp. 25-31, 2005.
M. Berlingerio, Coscia, M., Giannotti, F., Monreale, A., and Pedreschi, D., Evolving networks: Eras and turning points, Intell. Data Anal., vol. 17, pp. 27–48, 2013.
N. Forgó, Hänold, S., van den Hoven, J., Krügel, T., Lishchuk, I., Mahieu, R., Monreale, A., Pedreschi, D., Pratesi, F., and van Putten, D., An ethico-legal framework for social data science, 2020.
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. 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.

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