Publications

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Journal Article
A. Sirbu, Ruskin, H. J., and Crane, M., Cross-platform microarray data normalisation for regulatory network inference., PLoS One, vol. 5, p. e13822, 2010.
F. Bonchi, Giannotti, F., Lucchese, C., Orlando, S., Perego, R., and Trasarti, R., A constraint-based querying system for exploratory pattern discovery, Inf. Syst., vol. 34, pp. 3-27, 2009.
F. Bonchi, Giannotti, F., Lucchese, C., Orlando, S., Perego, R., and Trasarti, R., A constraint-based querying system for exploratory pattern discovery, Inf. Syst., vol. 34, pp. 3-27, 2009.
V. Bogorny, Renso, C., de Aquino, A. R., de Siqueira, F. L., and Alvares, L. O., CONSTAnT - A Conceptual Data Model for Semantic Trajectories of Moving Objects , Transaction in GIS, 2013.
G. Rossetti, Citraro, S., and Milli, L., Conformity: A Path-Aware Homophily Measure for Node-Attributed Networks, arXiv preprint arXiv:2012.05195, 2020.
G. Rossetti, Citraro, S., and Milli, L., Conformity: a Path-Aware Homophily measure for Node-Attributed Networks, IEEE Intelligent SystemsIEEE Intelligent Systems, pp. 1 - 1, 2021.
S. Ruggieri, Eirinakis, P., Subramani, K., and Wojciechowski, P., On the complexity of quantified linear systems, Theoretical Computer Science, vol. 518, pp. 128–134, 2014.
P. Mancarella, Martini, S., and Pedreschi, D., Complete Logic Programs with Domain-Closure Axiom, J. Log. Program., vol. 5, pp. 263-276, 1988.
A. Sirbu, Ruskin, H. J., and Crane, M., Comparison of evolutionary algorithms in gene regulatory network model inference., BMC Bioinformatics, vol. 11, p. 59, 2010.
G. Rossetti and Cazabet, R., Community Discovery in Dynamic Networks: a Survey, Journal ACM Computing Surveys, vol. 51, 2018.
A. Sirbu, Loreto, V., Servedio, V. D. P., and Tria, F., Cohesion, consensus and extreme information in opinion dynamics, Advances in Complex Systems, vol. 16, p. 1350035, 2013.
S. Marina Joseph, Citraro, S., Morini, V., Rossetti, G., and Stella, M., Cognitive network science quantifies feelings expressed in suicide letters and Reddit mental health communities, arXiv preprint arXiv:2110.15269, 2021.
K. R. Apt, Gabbrielli, M., and Pedreschi, D., A Closer Look at Declarative Interpretations, J. Log. Program., vol. 28, pp. 147-180, 1996.
M. Coscia, Giannotti, F., and Pedreschi, D., A classification for community discovery methods in complex networks, Statistical Analysis and Data Mining, vol. 4, pp. 512-546, 2011.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., Classes of Terminating Logic Programs, CoRR, vol. cs.LO/0106, 2001.
D. Pedreschi, Ruggieri, S., and Smaus, J. - G., Classes of terminating logic programs, TPLP, vol. 2, pp. 369-418, 2002.
G. Rossetti, Milli, L., and Cazabet, R., CDLIB: a python library to extract, compare and evaluate communities from complex networks, Applied Network Science, vol. 4, p. 52, 2019.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, Journal of Intelligent Information Systems, pp. 1–13, 2019.
B. Qureshi, Kamiran, F., Karim, A., Ruggieri, S., and Pedreschi, D., Causal inference for social discrimination reasoning, vol. 54, pp. 425 - 437, 2020.
B. Qureshi, Kamiran, F., Karim, A., and Ruggieri, S., Causal Discrimination Discovery Through Propensity Score Analysis, arXiv preprint arXiv:1608.03735, 2016.
D. Pedreschi and Ruggieri, S., Bounded Nondeterminism of Logic Programs, Ann. Math. Artif. Intell., vol. 42, pp. 313-343, 2004.
S. Bergamaschi, Carlini, E., Ceci, M., Furletti, B., Giannotti, F., Malerba, D., Mezzanzanica, M., Monreale, A., Pasi, G., Pedreschi, D., Perego, R., and Ruggieri, S., Big Data Research in Italy: A Perspective, Engineering, vol. 2, p. 163, 2016.
A. Balliu, Olivetti, D., Babaoglu, O., Marzolla, M., and Sirbu, A., A Big Data Analyzer for Large Trace Logs, Computing, 2015.
E. Ntoutsi, Fafalios, P., Gadiraju, U., Iosifidis, V., Nejdl, W., Vidal, M. - E., Ruggieri, S., Turini, F., Papadopoulos, S., Krasanakis, E., and others, Bias in data-driven artificial intelligence systems—An introductory survey, Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, vol. 10, p. e1356, 2020.
F. Bodria, Giannotti, F., Guidotti, R., Naretto, F., Pedreschi, D., and Rinzivillo, S., Benchmarking and Survey of Explanation Methods for Black Box Models, CoRR, vol. abs/2102.13076, 2021.

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