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- W2059292748 abstract "Typically graph-clustering approaches assume that a cluster is a vertex subset such that for all of its vertices, the number of links connecting a vertex to its cluster is higher than the number of links connecting the vertex to the remaining graph. We consider a cluster such that for all of its vertices, the number of links connecting a vertex to its cluster is higher than the number of links connecting the vertex to any other cluster. Based on this fundamental view, we propose a graph-clustering algorithm that identifies clusters even if they contain vertices more strongly connected outside than inside their cluster; hence, the proposed algorithm is proved exceptionally efficient in clustering densely interconnected graphs. Extensive experimentation with artificial and real datasets shows that our approach outperforms earlier alternate clustering techniques." @default.
- W2059292748 created "2016-06-24" @default.
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- W2059292748 date "2010-05-01" @default.
- W2059292748 modified "2023-09-25" @default.
- W2059292748 title "Clustering dense graphs: A web site graph paradigm" @default.
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- W2059292748 doi "https://doi.org/10.1016/j.ipm.2009.11.003" @default.
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