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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.
A. Lulli, Gabrielli, L., Dazzi, P., Dell'Amico, M., Michiardi, P., Nanni, M., and Ricci, L., Scalable and flexible clustering solutions for mobile phone-based population indicators, I. J. Data Science and Analytics, vol. 4, pp. 285–299, 2017.
C. Lucchese, Bonchi, F., Giannotti, F., Orlando, S., Perego, R., and Trasarti, R., On Interactive Pattern Mining from Relational Databases, in SEBD, 2006, pp. 329-338.
V. M. de Lira, Rinzivillo, S., Renso, C., Times, V. C., and Tedesco, P. {\'ı}ciaC. A. R., Investigating semantic regularity of human mobility lifestyle, in 18th International Database Engineering {&} Applications Symposium, {IDEAS} 2014, Porto, Portugal, July 7-9, 2014, Porto, Portugal, 2014, pp. 314–317.
V. M. de Lira, Rinzivillo, S., Times, V. C., and Renso, C., {MAPMOLTY:} {A} Web Tool for Discovering Place Loyalty Based on Mobile Crowdsource Data, in Web Engineering, 14th International Conference, {ICWE} 2014, Toulouse, France, July 1-4, 2014. Proceedings, 2014, pp. 528–531.
V. M. de Lira, Times, V. C., Renso, C., and Rinzivillo, S., ComeWithMe: An Activity-Oriented Carpooling Approach, in 2015 {IEEE} 18th International Conference on Intelligent Transportation Systems, 2015.
F. Lillo and Ruggieri, S., Estimating the Total Volume of Queries to a Search Engine, IEEE Transactions on Knowledge and Data Engineering, pp. 1-1, 2021.
L. Leone, Marchitiello, M., Natilli, M., and Romano, M. Francesca, Measuring the effectiveness of homeopathic care through objective and shared indicators, Homeopathy, vol. 100, pp. 212–219, 2011.
O. Lampridis, Guidotti, R., and Ruggieri, S., Explaining Sentiment Classification with Synthetic Exemplars and Counter-Exemplars, in Discovery Science, Cham, 2020.