Reporting Flock Patterns

  • Marc Benkert
  • Joachim Gudmundsson
  • Florian Hübner
  • Thomas Wolle
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4168)


Data representing moving objects is rapidly getting more available, especially in the area of wildlife GPS tracking. It is a central belief that information is hidden in large data sets in the form of interesting patterns. One of the most common spatio-temporal patterns sought after is flocks. A flock is a large enough subset of objects moving along paths close to each other for a certain pre-defined time. We give a new definition that we argue is more realistic than the previous ones, and we present fast approximation algorithms to report flocks. The algorithms are analysed both theoretically and experimentally.


Approximation Algorithm Query Range Polygonal Line Pruning Method Query Region 
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 2006

Authors and Affiliations

  • Marc Benkert
    • 1
  • Joachim Gudmundsson
    • 2
  • Florian Hübner
    • 1
  • Thomas Wolle
    • 2
  1. 1.Department of Computer ScienceKarlsruhe UniversityKarlsruheGermany
  2. 2.National ICT Australia LtdAlexandriaAustralia

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