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Mining Spatial-temporal Clusters from Geo-databases

  • Min Wang
  • Aiping Wang
  • Anbo Li
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4093)

Abstract

In order to mine spatial-temporal clusters from geo-databases, two clustering methods with close relationships are proposed, which are both based on neighborhood searching strategy, and rely on the sorted k-dist graph to automatically specify their respective algorithm arguments. We declare the most distinguishing advantage of our clustering methods is they avoid calculating the spatial-temporal distance between patterns which is a tough job. Our methods are validated with the successful extraction of seismic sequence from seismic databases, which is a typical example of spatial–temporal clusters.

Keywords

Seismic Event Distance Threshold Seismic Sequence Temporal Cluster China Seismological Bureau 
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

  • Min Wang
    • 1
  • Aiping Wang
    • 1
  • Anbo Li
    • 1
  1. 1.College of Geography ScienceNanjing Normal UniversityNanjingChina

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