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- W2393574570 abstract "For large-scale graph data,most of algorithms of graph clustering suffered from poor scalablity on the complexity of time and space,and were prone to over-fine-grained clusters.In this paper the concept called k-layers neighbors is proposed to avoid over-fine-grained clusters caused by single-layer neighborhood.A distributed clustering algorithm based on cut set is proposed.It adopt a searching strategy of minimum cost cut set based on graph connectivity,to reduce the association of graph fragments and improve parallelism and scalablity of clustering.With the extensive experiments on real data,it shows that the proposed algorithm achieves the better efficiency of time and space and the effective of clusters." @default.
- W2393574570 created "2016-06-24" @default.
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- W2393574570 date "2013-01-01" @default.
- W2393574570 modified "2023-09-23" @default.
- W2393574570 title "Study of Efficient Clustering Algorithm on Large Graphs" @default.
- W2393574570 hasPublicationYear "2013" @default.
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