FlexTrack: a system for querying flexible patterns in trajectory databases
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
Adaptive non-parametric identification of dense areas using cell phone records for urban analysis
Engineering Applications of Artificial Intelligence
Inferring human mobility patterns from anonymized mobile communication usage
Proceedings of the 10th International Conference on Advances in Mobile Computing & Multimedia
Combining Spatial Proximity and Temporal Continuity for Learning Invariant Representations
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
A survey on smartphone-based systems for opportunistic user context recognition
ACM Computing Surveys (CSUR)
The influence of social norms on synchronous versus asynchronous communication technologies
Proceedings of the 1st ACM international workshop on Personal data meets distributed multimedia
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Call Detail Record (CDR) databases contain many millions of records with information about mobile phone calls, including the users' location when the call was made/received. This huge amount of spatio-temporal data opens the door for the study of human trajectories on a large scale without the bias that other sources, like GPS or WLAN networks, introduce in the population studied. Furthermore, it provides a platform for the development of a wide variety of studies ranging from the spread of diseases to planning of public transportation. Nevertheless, previous work on spatio-temporal queries does not provide a framework "flexible" enough for expressing the complexity of human trajectories. In this paper we present Spatio-Temporal Pattern System (STPS) to query spatio-temporal patterns in very large CDR databases. STPS uses a regular-expression query language that is intuitive and that allows for any combination of spatial and temporal predicates with constraints, including the use of variables. The design of the language takes into consideration the layout of the areas being covered by the cellular towers, as well as "areas" that label places of interested (e.g. neighborhoods, parks, etc). A full implementation of the STPS is currently running with real, very large CDR databases at Telefonica Research Labs. An extensive performance evaluation of the STPS shows that it can efficiently find very complex mobility patterns in large CDR databases.