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Detecting Commuting Patterns by Clustering Subtrajectories

  • Kevin Buchin
  • Maike Buchin
  • Joachim Gudmundsson
  • Maarten Löffler
  • Jun Luo
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5369)

Abstract

In this paper we consider the problem of detecting commuting patterns in a trajectory. For this we search for similar subtrajectories. To measure spatial similarity we choose the Fréchet distance and the discrete Fréchet distance between subtrajectories, which are invariant under differences in speed. We give several approximation algorithms, and also show that the problem of finding the ‘longest’ subtrajectory cluster is as hard as MaxClique to compute and approximate.

Keywords

Free Space Reference Trajectory Outgoing Edge Full Version Event Point 
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 2008

Authors and Affiliations

  • Kevin Buchin
    • 1
  • Maike Buchin
    • 1
  • Joachim Gudmundsson
    • 2
  • Maarten Löffler
    • 1
  • Jun Luo
    • 1
  1. 1.Inst. for Information and Computing SciencesUtrecht UniversityThe Netherlands
  2. 2.NICTASydneyAustralia

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