Contributo in atti di convegno, 2011, ENG, 10.1145/2020408.2020591

Mining mobility user profiles for car pooling

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

Keywords

spatio-temporal data mining, mobility, application, trajectory patter

CNR authors

Pinelli Fabio, Giannotti Fosca, Nanni Mirco, Trasarti Roberto

CNR institutes

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