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Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs.

Authors :
Sungjun Lee
Junseok Lim
Jonghun Park
Kwanho Kim
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