Learning Trajectory Information with Neural Networks and the Markov Model to Develop Intelligent Location-Based Services

Sang-Jun Han () and Sung-Bae Cho ()
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Sang-Jun Han: Digital Media R&D Center, Samsung Electronics Co., Ltd., Maetan3-Dong, Yeongtong-Gu, Suwon-City, Gyeonggi-Do 443-742, Korea
Sung-Bae Cho: Department of Computer Science, Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, Seoul 120-749, Korea

Journal of Information & Knowledge Management (JIKM), 2006, vol. 05, issue 04, 291-301

Abstract: In the development of location-based services, various location-sensing techniques and experimental/commercial services have been used. However, conventional location-based services are limited in terms of flexibility because they depend on the current location of the user. We propose a novel method of predicting the user's future movements in order to develop advanced location-based services. The user's movement trajectory is modelled using a combination of recurrent self-organising maps (RSOM) and the Markov model. Future movement is predicted based on past movement trajectories. A prototype application based on location prediction is also presented. This application is a mobile user assistant targeted to university students. To verify the proposed method, a GPS dataset was collected on the Yonsei University campus. The results were promising enough to confirm that the application works flexibly even in ambiguous situations.

Keywords: Location-based services; context-awareness; self-organising map; Markov chain model (search for similar items in EconPapers)
Date: 2006
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DOI: 10.1142/S0219649206001554

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