计算机工程2012，Vol.38Issue(17)：56-58,62,4.DOI:10.3969/j.issn.1000-3428.2012.17.016
基于组合模型的局部搜索弱社团结构发现算法
Local Searching Weak Community Structure Discovery Algorithm Based on Combinatorial Model
叶慧 1李旻1
作者信息
- 1. 华南师范大学计算机科学系,广州510631
- 折叠
摘要
Abstract
Existing complex network community algorithms mostly take the global modularity as a criterion of searching the best community structure. However, it is revealed to suffer a resolution limit that may fail to discover small known qualified communities and discover some unqualified communities. Aiming at this problem, combining weak community definition, local fitness and global modularity, this paper presents a new multi-objective integer programming model and an efficient heuristic algorithm. It successfully discovers networks' hierarchical and overlapping community structure. Experimental results show that the algorithm overcomes the disadvantages and fully discovers small communities with high efficiency.
关键词
复杂网络/弱社团结构/全局模块度/局部适应度/多目标整数规划Key words
complex network/ weak community structure/ global modularity/ local fitness/ multi-objective integer programming
分类
信息技术与安全科学引用本文复制引用
叶慧,李旻..基于组合模型的局部搜索弱社团结构发现算法[J].计算机工程,2012,38(17):56-58,62,4.
