Context-Aware Similarity of Trajectories

  • Maike Buchin
  • Somayeh Dodge
  • Bettina Speckmann
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7478)

Abstract

The movement of animals, people, and vehicles is embedded in a geographic context. This context influences the movement. Most analysis algorithms for trajectories have so far ignored context, which severely limits their applicability. In this paper we present a model for geographic context that allows us to integrate context into the analysis of movement data. Based on this model we develop simple but efficient context-aware similarity measures. We validate our approach by applying these measures to hurricane trajectories.

Keywords

Movement data geographic context similarity measures 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Maike Buchin
    • 1
  • Somayeh Dodge
    • 2
  • Bettina Speckmann
    • 1
  1. 1.Dept. of Mathematics and Computer ScienceTU EindhovenThe Netherlands
  2. 2.Dept. of Civil, Environmental, and Geodetic EngineeringOhio State UniversityUSA

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