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Sensors 2016, 16(2), 145; doi:10.3390/s16020145

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

1
Department of Industrial Engineering, Seoul National University, 1 Gwanak-ro, Gwanak-gu, Seoul 08826, Korea
2
Department of Industrial & Management Engineering, Incheon National University, 119 Academy-ro, Yeonsu-gu, Incheon 22012, Korea
*
Author to whom correspondence should be addressed.
Academic Editor: Leonhard M. Reindl
Received: 1 October 2015 / Revised: 28 December 2015 / Accepted: 20 January 2016 / Published: 23 January 2016
(This article belongs to the Section Sensor Networks)
View Full-Text   |   Download PDF [672 KB, uploaded 23 January 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. View Full-Text
Keywords: next place prediction; movement patterns; spatiotemporal patterns; Markov chain; gapped sequence mining next place prediction; movement patterns; spatiotemporal patterns; Markov chain; gapped sequence mining
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Lee, S.; Lim, J.; Park, J.; Kim, K. Next Place Prediction Based on Spatiotemporal Pattern Mining of Mobile Device Logs. Sensors 2016, 16, 145.

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