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On Mining Group Patterns of Mobile Users

  • Yida Wang
  • Ee-Peng Lim
  • San-Yih Hwang
Conference paper
  • 559 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2736)

Abstract

In this paper, we present a group pattern mining approach to derive the grouping information of mobile device users based on the spatio-temporal distances among them. Group patterns of users are determined by a distance threshold and a minimum duration. To discover group patterns, we propose the AGP and VG-growth algorithms that are derived from the Apriori and FP-growth algorithms respectively. We further evaluate the efficiencies of these two algorithms using synthetically generated user movement data.

Keywords

Association Rule Mobile User Group Pattern User Movement Distinct User 
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 2003

Authors and Affiliations

  • Yida Wang
    • 1
  • Ee-Peng Lim
    • 1
  • San-Yih Hwang
    • 2
  1. 1.Centre for Advanced Information Systems, School of Computer EngineeringNanyang Technological University, SingaporeSingapore
  2. 2.Department of Information ManagementNational Sun Yat-Sen UniversityKaohsiungTaiwan 80424

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