2011 MiningMobilityUserProfilesforCa

• (Trasarti et al., 2011) ⇒ Roberto Trasarti, Fabio Pinelli, Mirco Nanni, and Fosca Giannotti. (2011). “Mining Mobility User Profiles for Car Pooling.” In: Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2011) Journal. ISBN:978-1-4503-0813-7 doi:10.1145/2020408.2020591

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222011%22+Mining+Mobility+User+Profiles+for+Car+Pooling
• http://dl.acm.org/citation.cfm?id=2020408.2020591&preflayout=flat#citedby

Quotes

Author Keywords

• Algorithms; data mining; spatio-temporal data mining; trajectory pattern; user profiles and alert services

Abstract

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.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2011 MiningMobilityUserProfilesforCa	Fabio Pinelli Roberto Trasarti Fosca Giannotti Mirco Nanni			Mining Mobility User Profiles for Car Pooling				10.1145/2020408.2020591		2011