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Istituto di Scienza e Tecnologie dell'Informazione     
Trasarti R., Pinelli F., Nanni M., Giannotti F. Mining mobility user profiles for car pooling. In: KDD '11 - 17th ACM SIGKDD international conference on Knowledge discovery and data mining (San Diego, CA, USA, 21-08 2011). Proceedings, pp. 1190 - 1198. ACM, 2011.
 
 
Abstract
(English)
In this paper we introduce a methodology for extracting mobility profiles of individuals from raw digital traces (in particular, GPS traces), and study criteria to match individuals based on profiles. We instantiate the profile matching problem to a specific application context, namely proactive car pooling services, and therefore develop a matching criterion that satisfies various basic constraints obtained from the background knowledge of the application domain. In order to evaluate the impact and robustness of the methods introduced, two experiments are reported, which were performed on a massive dataset containing GPS traces of private cars: (i) the impact of the car pooling application based on profile matching is measured, in terms of percentage shareable traffic; (ii) the approach is adapted to coarser-grained mobility data sources that are nowadays commonly available from telecom operators. In addition the ensuing loss in precision and coverage of profile matches is measured.
URL: http://doi.acm.org/10.1145/2020408.2020591
DOI: 10.1145/2020408.2020591
Subject spatio-temporal data mining
mobility
application
trajectory patter
H.2.8 Database Applications
62-07 Data analysis


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