Finding Representative Nodes in Probabilistic Graphs

author: Laura Langohr, University of Helsinki
published: Oct. 20, 2009,   recorded: September 2009,   views: 3259


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We introduce the problem of identifying representative nodes in probabilistic graphs, motivated by the need to produce di fferent simple views to large networks. We defi ne a probabilistic similarity measure for nodes, and then apply clustering methods to nd 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.

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