Exploiting Multiple Radii to Learn Significant Locations

  • Norio Toyama
  • Takashi Ota
  • Fumihiro Kato
  • Youichi Toyota
  • Takashi Hattori
  • Tatsuya Hagino
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3479)

Abstract

Location contexts are important for many context-aware applications. A significant location is a specialized form of location context for expressing a user’s daily activity. We propose a method to cluster positions measured by cellular phones into significant locations with multiple radii. Cellular phones we used are equipped with a positioning system, where data can be taken in low frequency with wide-varying estimated errors. In order to learn significant locations, our system exploits multiple radii for coping with these characteristics and for adapting to a variety of users’ spatial behavioral patterns. We also discuss appropriate parameters for our clustering method.

Keywords

Location Candidate Cellular Phone Spatial Behavior Threshold Density Ubiquitous Environment 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Norio Toyama
    • 1
  • Takashi Ota
    • 1
  • Fumihiro Kato
    • 1
  • Youichi Toyota
    • 1
  • Takashi Hattori
    • 2
  • Tatsuya Hagino
    • 2
  1. 1.Graduate School of Media and GovernanceKeio UniversityKanagawaJapan
  2. 2.Faculty of Environmental InformationKeio UniversityKanagawaJapan

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