计算机工程与科学2018，Vol.40Issue(12)：2258-2264,7.DOI:10.3969/j.issn.1007-130X.2018.12.022
一种基于局部扩展优化的重叠社区发现算法
An overlapping community detection algorithm based on local expansion optimization
摘要
Abstract
Overlapping community structure detection bears both theoretical and practical significance for the study of complex systems.We propose an overlapping community detection algorithm based on local expansion optimization.Firstly, agroup of irrelevant seeds with large clustering coefficient are selected as initial communities according to the clustering coefficient of network nodes.Then, the initial communities are expanded into tightly-connected local communities by agreedy strategy.Finally, similar communities are merged and overlapping community structures with high cover rate are obtained.Experimental results on both synthetic and real-world networks show that compared with other representative local expansion methods, the proposed algorithm can efficiently detect overlapping communities of higher quality in the networks with different sparsity degrees.关键词
复杂网络/重叠社区发现/局部扩展/结构适应度Key words
complex network/overlapping community detection/local expansion/structural fitness分类
信息技术与安全科学引用本文复制引用
李慧,杨青泉,王慧慧..一种基于局部扩展优化的重叠社区发现算法[J].计算机工程与科学,2018,40(12):2258-2264,7.基金项目
国家社会科学基金(17BXW069) （17BXW069）
