Geographic Privacy-aware Knowledge Discovery and Delivery

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The technologies of mobile communications and ubiquitous computing pervade our society, and wireless networks sense the movement of people and vehicles, generating large volumes of mobility data. Miniaturization, wearability, pervasiveness is producing traces of our mobile activity, with increasing positioning accuracy and semantic richness: Location data from mobile phones: (GSM cell positions), GPS tracks from mobile devices receiving geo-positions from satellites, etc. The objective of the GeoPKDD project is to discover useful knowledge about human movement behavior from mobility data, while preserving the privacy of the people under observation. While pursuing this ambitious objective, the GeoPKDD project has started a new exciting multidisciplinary research area, at the crossroads of mobility, data mining, and privacy. Relevant Documents
Furletti, B., M. Gabbrielli, 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.
Giannotti, F., M. Nanni, D. Pedreschi, C. Renso, S. Rinzivillo, and R. Trasarti, "GeoPKDD – Geographic Privacy-aware Knowledge Discovery", The European Future Technologies Conference (FET 2009), 2009.
Andrienko, G., N. Andrienko, S. Rinzivillo, M. Nanni, D. Pedreschi, and F. Giannotti, "Visual Cluster Analysis of Large Collections of Trajectories", IEEE Visual Analytics Science and Tecnology (VAST 2009): IEEE Computer Society Press, 2009.
Monreale, A., F. Pinelli, R. Trasarti, and F. Giannotti, "WhereNext: a Location Predictor on Trajectory Pattern Mining", 15th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2009.
Pensa, R. G., A. Monreale, F. Pinelli, and D. Pedreschi, "Anonymous Sequences from Trajectory Data", 17th Italian Symposium on Advanced Database Systems, 17, Camogli, Italy, 2009.
Rinzivillo, S., F. Turini, V. Bogorny, C. Körner, B. Kuijpers, and M. May, "Knowledge Discovery from Geographical Data", Mobility, Data Mining and Privacy, pp. 243-265, 2008.
Pinelli, F., A. Monreale, R. Trasarti, and F. Giannotti, "Location prediction within the mobility data analysis environment Daedalus", First International Workshop on Computational Transportation Science, Dublin, Ireland, 2008.
Rinzivillo, S., D. Pedreschi, M. Nanni, F. Giannotti, N. Andrienko, and G. Andrienko, "Visually driven analysis of movement data by progressive clustering", Information Visualization, vol. 7, no. 3-4: Palgrave Macmillan Ltd, pp. 225-239, 2008.


Image by Photo: Fabio Venni - Artwork and Design: Isabel Meirelles, Art Design, Northeastern University, Boston,
Web Site
Start Date
1 December 2005
End Date
31 March 2009
Department of Computer Science, University of Pisa (DI-UNIPI)
Istituto di Scienza e Tecnologie dell’Informazione, National Research Council of Italy (ISTI-CNR)