吉首大学学报（自然科学版）2023，Vol.44Issue(6)：9-13,19,6.DOI:10.13438/j.cnki.jdzk.2023.06.002
基于谱聚类的二分网络社团检测算法
Community Detection Algorithm for Bipartite Networks Based on Spectral Clustering
摘要
Abstract
In order to solve the problem of low precision and original network information lose in commu-nity 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 partitio-ning problems.Experimental results show that,the SVD-MS algorithm can effectively partition the com-munity structure of bipartite networks and preserve the original network information.关键词
二分网络/社团检测/模块度/奇异值分解Key words
bipartite network/community detection/modularity/singular value decomposition分类
计算机与自动化引用本文复制引用
刘晨晨,许英..基于谱聚类的二分网络社团检测算法[J].吉首大学学报（自然科学版）,2023,44(6):9-13,19,6.基金项目
国家自然科学基金资助项目(72164034) （72164034）
