Community Detection Algorithm for Bipartite Networks Based on Spectral Clustering

doi:10.13438/j.cnki.jdzk.2023.06.002

Abstract

Abstract: In order to solve the problem of low precision and original network information lose in community detection of bipartite network,a new spectral clustering algorithm named SVD-MS is proposed.This method maps Barber's problem of maximizing the module size of bipartite networks to the problem of singular value vector decomposition,and combines heuristic algorithms to quickly solve vector partitioning problems.Experimental results show that,the SVD-MS algorithm can effectively partition the community structure of bipartite networks and preserve the original network information.

Key words: bipartite network, community detection, modularity, singular value decomposition

LIU Chenchen, XU Ying. Community Detection Algorithm for Bipartite Networks Based on Spectral Clustering[J]. Journal of Jishou University(Natural Sciences Edition), 2023, 44(6): 9-13.

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