Finding Representative Nodes in Probabilistic Graphs

  • Laura Langohr
  • Hannu Toivonen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7250)


We introduce the problem of identifying representative nodes in probabilistic graphs, motivated by the need to produce different simple views to large BisoNets. We define a probabilistic similarity measure for nodes, and then apply clustering methods to find groups of nodes. Finally, a representative is output from each cluster. We report on experiments with real biomedical data, using both the k-medoids and hierarchical clustering methods in the clustering step. The results suggest that the clustering based approaches are capable of finding a representative set of nodes.


Good Path Network Reliability Hierarchical Cluster Method Hierarchical Method Probabilistic Graph 
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

© The Author(s) 2012 2012

Authors and Affiliations

  • Laura Langohr
    • 1
  • Hannu Toivonen
    • 1
  1. 1.Department of Computer Science and Helsinki Institute for Information Technology HIITUniversity of HelsinkiFinland

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