Contributo in atti di convegno, 2011, ENG, 10.1145/2020408.2020591
Trasarti, Roberto; Pinelli, Fabio; Nanni, Mirco; Giannotti, Fosca
CNR-ISTI, Pisa
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.
17th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '11. ACM Press : New York (Stati Uniti d'America), pp. 1190–1198, San Diego, CA, USA, 21-08 2011
spatio-temporal data mining, mobility, application, trajectory patter
Pinelli Fabio, Giannotti Fosca, Nanni Mirco, Trasarti Roberto
ISTI – Istituto di scienza e tecnologie dell'informazione "Alessandro Faedo"
ID: 206348
Year: 2011
Type: Contributo in atti di convegno
Creation: 2013-03-11 13:43:16.000
Last update: 2016-03-29 12:26:02.000
External IDs
CNR OAI-PMH: oai:it.cnr:prodotti:206348
DOI: 10.1145/2020408.2020591
Scopus: 2-s2.0-80052654177
PUMA: 2011-A2-107