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Real Time Detection and Tracking of Spatial Event Clusters

  • Natalia AndrienkoEmail author
  • Gennady Andrienko
  • Georg Fuchs
  • Salvatore Rinzivillo
  • Hans-Dieter Betz
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9286)

Abstract

We demonstrate a system of tools for real-time detection of significant clusters of spatial events and observing their evolution. The tools include an incremental stream clustering algorithm, interactive techniques for controlling its operation, a dynamic map display showing the current situation, and displays for investigating the cluster evolution (time line and space-time cube).

Keywords

Real Time Detection Stream Cluster Offline Phase Evolve Data Stream Member Event 
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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References

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    Bouguelia M.-R., Belaïd Y., Belaïd, A.: An adaptive incremental clustering method based on the growing neural gas algorithm. In: Proc. 2nd Int. Conf. Pattern Recognition Applications and Methods - ICPRAM 2013, pp. 42–49 (2013)Google Scholar

Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Natalia Andrienko
    • 1
    • 2
    Email author
  • Gennady Andrienko
    • 1
    • 2
  • Georg Fuchs
    • 1
  • Salvatore Rinzivillo
    • 3
  • Hans-Dieter Betz
    • 4
  1. 1.Fraunhofer Institute IAISSankt AugustinGermany
  2. 2.City University LondonLondonUK
  3. 3.CNR ISTIPisaItaly
  4. 4.nowcast GmbHMunichGermany

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