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G. Rossetti and Cazabet, R., “Community Discovery in Dynamic Networks: a Survey”, Journal ACM Computing Surveys, vol. 51, 2018.
G. Rossetti, Guidotti, R., Miliou, I., Pedreschi, D., and Giannotti, F., “A supervised approach for intra-/inter-community interaction prediction in dynamic social networks”, Social Network Analysis and Mining, vol. 6, p. 86, 2016.
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.
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, 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, pp. 1–19, 2017.
G. Rossetti, Milli, L., Citraro, S., and Morini, V., “UTLDR: an agent-based framework for modeling infectious diseases and public interventions”, arXiv preprint arXiv:2011.05606, 2020.
G. Rossetti, Milli, L., Rinzivillo, S., Sirbu, A., Pedreschi, D., and Giannotti, F., “NDlib: Studying Network Diffusion Dynamics”, in IEEE International Conference on Data Science and Advanced Analytics, DSA, Tokyo, 2017.
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.
G. Rossetti, “ANGEL: efficient, and effective, node-centric community discovery in static and dynamic networks”, Applied Network Science, vol. 5, pp. 1–23, 2020.
G. Rossetti, Morini, V., and Pollacci, L., “Capturing Political Polarization of Reddit Submissions in the Trump Era”, in SEBD, 2020.
G. Rossetti, Pedreschi, D., and Giannotti, F., “Node-centric Community Discovery: From static to dynamic social network analysis”, Online Social Networks and Media, vol. 3, pp. 32–48, 2017.
A. Romei and Ruggieri, S., “A multidisciplinary survey on discrimination analysis”, The Knowledge Engineering Review, vol. 29, pp. 582–638, 2014.
A. Romei, Ruggieri, S., and Turini, F., “Discrimination discovery in scientific project evaluation: A case study”, Expert Systems with Applications, vol. 40, pp. 6064–6079, 2013.
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.
M. Francesca Romano and Natilli, M., “Wine tourism in Italy: New profiles, styles of consumption, ways of touring”, Turizam: međunarodni znanstveno-stručni časopis, vol. 57, pp. 463–475, 2009.
M. Francesca Romano and Natilli, M., “Wine and Food Tourism First European Conference”, Edizioni ETS Pisa, 2012.
S. Rinzivillo and Ruggieri, S., “Who/Where Are My New Customers?”, in ISMIS Industrial Session, 2011, pp. 307-317.
S. Rinzivillo, Mainardi, S., Pezzoni, F., Coscia, M., Giannotti, F., and Pedreschi, D., “Discovering the Geographical Borders of Human Mobility”, KI - Künstliche Intelligenz, 2012.
S. Rinzivillo, Turini, F., Bogorny, V., Körner, C., Kuijpers, B., and May, M., “Knowledge Discovery from Geographical Data”, in Mobility, Data Mining and Privacy, 2008, pp. 243-265.
S. Rinzivillo and Turini, F., “Knowledge discovery from spatial transactions”, Journal of Intelligent Information Systems, vol. 28, pp. 1-22, 2007.
S. Rinzivillo, de Siqueira, F. L., Gabrielli, L., Renso, C., and Bogorny, V., “Where Have You Been Today? Annotating Trajectories with DayTag”, in International Conference on Spatial and Spatio-temporal Databases (SSTD), 2013, pp. 467-471.
S. Rinzivillo, Pedreschi, D., Nanni, M., Giannotti, F., Andrienko, N., and Andrienko, G., “Visually driven analysis of movement data by progressive clustering”, Information Visualization, vol. 7, pp. 225-239, 2008.
S. Rinzivillo and Turini, F., “Extracting spatial association rules from spatial transactions”, in ACM GIS, 2005, pp. 79-86.
S. Rinzivillo and Turini, F., “Classification in Geographical Information Systems”, in PKDD, 2004, pp. 374-385.
S. Rinzivillo, Gabrielli, L., Nanni, M., Pappalardo, L., Pedreschi, D., and Giannotti, F., “The purpose of motion: Learning activities from Individual Mobility Networks”, in International Conference on Data Science and Advanced Analytics, {DSAA} 2014, Shanghai, China, October 30 - November 1, 2014, 2014.

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