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Finding Representative Nodes in Probabilistic Graphs

Finding Representative Nodes in Probabilistic Graphs

This video was recorded at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML PKDD), Bled 2009. We introduce the problem of identifying representative nodes in probabilistic graphs, motivated by the need to produce different simple views to large networks. We define 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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