Mobility, Data Mining & Privacy

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The objective of MODAP and MOVE projects is to stimulate an interdisciplinary research area combining a variety of disciplines such as data mining, geography, visualization, data/knowledge representation, and transforming them into a new context of mobility. MODAP has a particular emphasis on the social impact of privacy on people’s movement behaviour.
Pappalardo, L., F.. Simini, S. Rinzivillo, D. Pedreschi, and F. Giannotti, "Comparing General Mobility and Mobility by Car", Computational Intelligence and 11th Brazilian Congress on Computational Intelligence (BRICS-CCI CBIC), 2013 BRICS Congress on, Sept, 2013.
Furletti, B., L. Gabrielli, C. Renso, and S. Rinzivillo, "Identifying users profiles from mobile calls habits", ACM SIGKDD International Workshop on Urban Computing, Beijing, China, ACM New York, NY, USA ©2012, 2012.
Kisilevich, S., F. Mansmann, M. Nanni, and S. Rinzivillo, "Spatio-temporal clustering", Data Mining and Knowledge Discovery Handbook, pp. 855-874, 2010.
Monreale, A., G. Andrienko, N. V. Andrienko, F. Giannotti, D. Pedreschi, S. Rinzivillo, and S. Wrobel, "Movement Data Anonymity through Generalization", Transactions on Data Privacy, vol. 3, no. 2, pp. 91–121, 2010.
Image by Thomas Hawk CC BY-NC 2.0, via Flickr
Web Site
Start Date
1 January 2009
End Date
31 December 2012
Department of Computer Science, University of Pisa (DI-UNIPI)
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)