1. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.
- Author
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Sungjun Lee, Junseok Lim, Jonghun Park, and Kwanho Kim
- Subjects
SPATIOTEMPORAL processes ,STRUCTURAL frames ,CYCLES ,MOBILE operating systems ,ALGORITHMS - 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]
- Published
- 2016
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