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2015
P. Mukala, Cerone, A., and Turini, F., “An exploration of learning processes as process maps in FLOSS repositories”. 2015.
A. Romei, Ruggieri, S., and Turini, F., “The layered structure of company share networks”, in Data Science and Advanced Analytics (DSAA), 2015. 36678 2015. IEEE International Conference on, 2015.
P. Mukala, Cerone, A., and Turini, F., “Mining learning processes from FLOSS mailing archives”, in Conference on e-Business, e-Services and e-Society, 2015.
2016
B. Thanh Luong, Ruggieri, S., and Turini, F., “Classification Rule Mining Supported by Ontology for Discrimination Discovery”, in Data Mining Workshops (ICDMW), 2016 IEEE 16th International Conference on, 2016.
V. Grossi, Pedreschi, D., and Turini, F., “Data Mining and Constraints: An Overview”, in Data Mining and Constraint Programming, Springer International Publishing, 2016, pp. 25–48.
S. Ruggieri and Turini, F., “A KDD process for discrimination discovery”, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2016.
2017
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.
V. Grossi, Romei, A., and Turini, F., “Survey on using constraints in data mining”, Data Mining and Knowledge Discovery, vol. 31, pp. 424–464, 2017.
2018
R. Guidotti, Monreale, A., Ruggieri, S., Pedreschi, D., Turini, F., and Giannotti, F., “Local Rule-Based Explanations of Black Box Decision Systems”, 2018.
D. Pedreschi, Giannotti, F., Guidotti, R., Monreale, A., Pappalardo, L., Ruggieri, S., and Turini, F., “Open the Black Box Data-Driven Explanation of Black Box Decision Systems”, 2018.
R. Guidotti, Monreale, A., Ruggieri, S., Turini, F., Giannotti, F., and Pedreschi, D., “A survey of methods for explaining black box models”, ACM computing surveys (CSUR), vol. 51, p. 93, 2018.
2019
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.
D. Pedreschi, Giannotti, F., Guidotti, R., Monreale, A., Ruggieri, S., and Turini, F., “Meaningful explanations of Black Box AI decision systems”, in Proceedings of the AAAI Conference on Artificial Intelligence, 2019.
2020
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.
M. Setzu, Guidotti, R., Monreale, A., and Turini, F., “Global Explanations with Local Scoring”, in Machine Learning and Knowledge Discovery in Databases, Cham, 2020.
2021
M. Setzu, Guidotti, R., Monreale, A., Turini, F., Pedreschi, D., and Giannotti, F., “GLocalX - From Local to Global Explanations of Black Box AI Models”, vol. 294, p. 103457, 2021.

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