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Graph Clustering Using Distance-k Cliques

Software Demonstration
  • Jubin Edachery
  • Arunabha Sen
  • Franz J. Brandenburg
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1731)

Abstract

Identifying the natural clusters of nodes in a graph and treating them as supernodes or metanodes for a higher level graph (or an abstract graph) is a technique used for the reduction of visual complexity of graphs with a large number of nodes. In this paper we report on the implementation of a clustering algorithm based on the idea of distance-k cliques, a generalization of the idea of the cliques in graphs. The performance of the clustering algorithm on some large graphs obtained from the archives of Bell Laboratories is presented.

Keywords

Cluster Algorithm Abstract Graph Visual Complexity High Quality Solution Graph Cluster 
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.

References

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Copyright information

© Springer-Verlag Berlin Heidelberg 1999

Authors and Affiliations

  • Jubin Edachery
    • 1
  • Arunabha Sen
    • 1
  • Franz J. Brandenburg
    • 2
  1. 1.Department of Computer ScienceArizona State UniversityTempeUSA
  2. 2.Lehrstuhl für Informatik Universität PassauPassauGermany

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