Community detection based on Beetle Swarm Optimization

被引:0
|
作者
Zhuang, Li [1 ]
Yu, Lin [1 ]
Zhang, Jie [1 ]
机构
[1] Nanjing Univ Sci & Technol, Nanjing, Peoples R China
关键词
complex network; community detection; Beetle Swarm Optimization; modularity quantity; module density function; community integration;
D O I
10.1109/IAEAC54830.2022.9929691
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Community detection is of great significance to complex network. In response to community detection in complex network which has unknown number of communities, this paper proposed a new community detection approach with integration based on Beetle Swarm Optimization (BSO) and been named BSOI (Beetle Swarm Optimization with Integration). In the initialization of community division, community flag adapting node is adopted, which means the community flag of every node is initialized by its neighbor node. BSO is applied to optimize the community division. Then, we merge communities by the maximum module density increment. Experiments show that it can get a stable and effective result of community division quickly on both artificial and real-world social networks.
引用
收藏
页码:1171 / 1176
页数:6
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