摘要
针对常用的NG模块度存在分辨率限制,不能识别小于一定规模的社团的问题,提出了网络自然密度的定义,用以衡量网络的连接紧密程度,在此基础上构造了密度模块度函数来评估社团结构的划分;进一步分3种情况证明了密度模块度函数,克服了NG模块度函数的分辨率限制问题;最后通过人工网络和经典现实网络验证了密度模块度函数的有效性。
The most popular modularity optimization may fail to identify communities smaller than a scale.A natural density of networks is proposed for describing the degree of interconnectedness of modules.The density modularity function is constructed to evaluate the community structure partitioning based on the natural density.Three cases study proves that the density modularity function can overcome the resolution limit of NG’s modularity.The density modularity has been tested on both artificial networks and classical real-world networks.Computational results demonstrate the effectiveness of the density modularity.
出处
《电子科技大学学报》
EI
CAS
CSCD
北大核心
2012年第2期185-191,共7页
Journal of University of Electronic Science and Technology of China
基金
国家自然科学基金(71071096)
关键词
社团探测
复杂网络
模块度
自然密度
community detection
complex networks
modularity
natural density
