You are here

L. Pollacci, Guidotti, R., Rossetti, G., Giannotti, F., and Pedreschi, D., The Fractal Dimension of Music: Geography, Popularity and Sentiment Analysis, in International Conference on Smart Objects and Technologies for Social Good, 2018.
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.
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.
R. Guidotti, Soldani, J., Neri, D., Brogi, A., and Pedreschi, D., Helping your docker images to spread based on explainable models, in Joint European Conference on Machine Learning and Knowledge Discovery in Databases, 2018.
G. Amato, Candela, L., Castelli, D., Esuli, A., Falchi, F., Gennaro, C., Giannotti, F., Monreale, A., Nanni, M., Pagano, P., Pappalardo, L., Pedreschi, D., Pratesi, F., Rabitti, F., Rinzivillo, S., Rossetti, G., Ruggieri, S., Sebastiani, F., and Tesconi, M., How Data Mining and Machine Learning Evolved from Relational Data Base to Data Science, in A Comprehensive Guide Through the Italian Database Research Over the Last 25 Years, S. Flesca, Greco, S., Masciari, E., and Saccà, D., Eds. Cham: Springer International Publishing, 2018, pp. 287 - 306.
L. Pollacci, Guidotti, R., Rossetti, G., Giannotti, F., and Pedreschi, D., The italian music superdiversity, Multimedia Tools and Applications, pp. 1–23, 2018.
R. Guidotti, Monreale, A., and Rinzivillo, S., Learning Data Mining, in 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA)2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), 2018.
R. Guidotti, Monreale, A., Ruggieri, S., Pedreschi, D., Turini, F., and Giannotti, F., Local Rule-Based Explanations of Black Box Decision Systems, 2018.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., NDlib: a python library to model and analyze diffusion processes over complex networks, International Journal of Data Science and Analytics, vol. 5, pp. 61–79, 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, Rossetti, G., Pappalardo, L., Giannotti, F., and Pedreschi, D., Personalized Market Basket Prediction with Temporal Annotated Recurring Sequences, IEEE Transactions on Knowledge and Data Engineering, 2018.
F. Pratesi, Monreale, A., Trasarti, R., Giannotti, F., Pedreschi, D., and Yanagihara, T., PRUDEnce: a system for assessing privacy risk vs utility in data sharing ecosystems, Transactions on Data Privacy, vol. 11, 2018.
F. Giannotti, Trasarti, R., Bontcheva, K., and Grossi, V., SoBigData: Social Mining & Big Data Ecosystem, in Companion of the The Web Conference 2018 on The Web Conference 2018, 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.
M. Ferretti, Barlacchi, G., Pappalardo, L., Lucchini, L., and Lepri, B., Weak nodes detection in urban transport systems: Planning for resilience in Singapore, in 2018 IEEE 5th international conference on data science and advanced analytics (DSAA), 2018.
M. Atzmueller, Becker, M., Molino, A., Mueller, J., Peters, J., and Sirbu, A., Applications for Environmental Sensing in EveryAware, in Participatory Sensing, Opinions and Collective Awareness, Springer, 2017, pp. 135–155.
R. Pellungrini, Pratesi, F., and Pappalardo, L., Assessing Privacy Risk in Retail Data, in Personal Analytics and Privacy. An Individual and Collective Perspective - First International Workshop, PAP 2017, Held in Conjunction with ECML PKDD 2017, Skopje, Macedonia, September 18, 2017, Revised Selected Papers, 2017.
C. Panigutti, Tizzoni, M., Bajardi, P., Smoreda, Z., and Colizza, V., Assessing the use of mobile phone data to describe recurrent mobility patterns in spatial epidemic models, Royal Society open science, vol. 4, p. 160950, 2017.
B. Dong, Wang, H. Wendy, Monreale, A., Pedreschi, D., Giannotti, F., and Guo, W., Authenticated Outlier Mining for Outsourced Databases, IEEE Transactions on Dependable and Secure Computing, 2017.
R. Guidotti, Monreale, A., Nanni, M., Giannotti, F., and Pedreschi, D., Clustering Individual Transactional Data for Masses of Users, in Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2017.
R. Pellungrini, Pappalardo, L., Pratesi, F., and Monreale, A., A Data Mining Approach to Assess Privacy Risk in Human Mobility Data, ACM Trans. Intell. Syst. Technol., vol. 9, pp. 31:1–31:27, 2017.
L. Pappalardo and Simini, F., Data-driven generation of spatio-temporal routines in human mobility, Data Mining and Knowledge Discovery, 2017.
B. Furletti, Trasarti, R., Cintia, P., and Gabrielli, L., Discovering and Understanding City Events with Big Data: The Case of Rome, Information, vol. 8, p. 74, 2017.
B. Guidi, Michienzi, A., and Rossetti, G., Dynamic community analysis in decentralized online social networks, in European Conference on Parallel Processing, 2017.
A. Baroni, Conte, A., Patrignani, M., and Ruggieri, S., Efficiently Clustering Very Large Attributed Graphs, arXiv preprint arXiv:1703.08590, 2017.