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Finding and Visualizing Graph Clusters Using PageRank Optimization

  • Fan Chung Graham
  • Alexander Tsiatas
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6516)

Abstract

We give algorithms for finding graph clusters and drawing graphs, highlighting local community structure within the context of a larger network. For a given graph G, we use the personalized PageRank vectors to determine a set of clusters, by optimizing the jumping parameter α subject to several cluster variance measures in order to capture the graph structure according to PageRank. We then give a graph visualization algorithm for the clusters using PageRank-based coordinates. Several drawings of real-world data are given, illustrating the partition and local community structure.

Keywords

Voronoi Diagram Spectral Cluster Graph Cluster Voronoi Region Representative Center 
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 2010

Authors and Affiliations

  • Fan Chung Graham
    • 1
  • Alexander Tsiatas
    • 1
  1. 1.Department of Computer Science and EngineeringUniversity of CaliforniaSan DiegoUSA

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