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A data driven approach for evaluating foundation skills of adults. (2017, April) Salvatori, E., Gabrielli, L. and Fosca Giannotti. Didamatica 2017.
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Furletti, B., Trasarti, R., Cintia, P. and Lorenzo Gabrielli. (2017,April). Discovering and Understanding City Events with Big Data. Journal on Big Data Analytics and Data-Driven Science 2017. MDPI.
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Lulli, A., Gabrielli, L., Dazzi, P., Dell'Amico, M., Michiardi, P., Nanni, M., Ricci, L. (2016, December). Scalable and flexible clustering solutions for mobile phone based population indicators. International Journal of Data Science and Analitics
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Calastri, C., Hess, S., Choudhury, C., Daly, A and L. Gabrielli. (2017, June). Developing mode choice models using semi-ubiquitous data sources: a case study using a smartphone based GPS survey from Italy. TRB.
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R. Campagni, L. Gabrielli, F. Giannotti , R. Guidotti, F. Maggino and D. Pedreschi: "Extracting Social Indicators from Big Data: an Experience in Measuring Wellbeing", In DATA SCIENCE & SOCIAL RESEARCH (DSSR).
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L. Gabrielli, G. Riccardi, L. Pappalardo: "Using retail market Big Data to nowcast Customer Price Index", SIS 2016
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Lorenzo Gabrielli, Davide Guido, Fosca Giannotti and Luca Bastiani. A Syntethic Measurement for Political Engagement of Spending: Pilot study to measure performance of local government using Open Government Data.
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Alessandro Lulli, Lorenzo Gabrielli, Matteo Dell’Amico, Pietro Michiardi, Mirco Nanni, Laura Ricci, Patrizio Dazzi. Improving Population Estimation From Mobile Calls: a Clustering Approach. ISCC 2016 The Twenty-First IEEE Symposium on Computers and
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Luca Pappalardo, Maarten Vanhoof, Lorenzo Gabrielli, Zbigniew Smoreda, Dino Pedreschi, Fosca Giannotti. An analytical framework to nowcast well-being using mobile phone data. International Journal of Data Science and Analytics. 2016.
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City users’ classification with mobile phone data
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Prof. Michele Migliore, Institute of Biophysics, National Research Council, Italy, State University of New York (SUNY), Downstate Health Science University, USA, "Computational Neuroscience", 16-20 March 2026
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