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Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.
- Source :
-
Sensors (14248220) . Feb2016, Vol. 16 Issue 2, p145. 19p. - Publication Year :
- 2016
-
Abstract
- Due to the recent explosive growth of location-aware services based on mobile devices, predicting the next places of a user is of increasing importance to enable proactive information services. In this paper, we introduce a data-driven framework that aims to predict the user's next places using his/her past visiting patterns analyzed from mobile device logs. Specifically, the notion of the spatiotemporal-periodic (STP) pattern is proposed to capture the visits with spatiotemporal periodicity by focusing on a detail level of location for each individual. Subsequently, we present algorithms that extract the STP patterns from a user's past visiting behaviors and predict the next places based on the patterns. The experiment results obtained by using a real-world dataset show that the proposed methods are more effective in predicting the user's next places than the previous approaches considered in most cases. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14248220
- Volume :
- 16
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- Sensors (14248220)
- Publication Type :
- Academic Journal
- Accession number :
- 113259041
- Full Text :
- https://doi.org/10.3390/s16020145