Learning trajectory information with neural networks and the markov model to develop intelligent location-based services

Sang Jun Han, Sung Bae Cho

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)

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.

Original languageEnglish
Pages (from-to)291-301
Number of pages11
JournalJournal of Information and Knowledge Management
Volume5
Issue number4
DOIs
Publication statusPublished - 2006

Bibliographical note

Funding Information:
This research was supported by the MIC (Ministry of Information and Communication), Korea, under the ITRC (Information Technology Research Center) support program supervised by the IITA (Institute of Information Technology Assessment), IITA-2006-(C1090-0603-0046).

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Computer Networks and Communications
  • Library and Information Sciences

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