Lanzhou University of Technology Institutional Repository (LUT_IR)
Community detection based on modularity density and genetic algorithm | |
Liu, Jinxia1,2; Zeng, Jianchao2 | |
2010 | |
会议录名称 | Proceedings - International Conference on Computational Aspects of Social Networks, CASoN'10
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页码 | 29-32 |
出版者 | IEEE Computer Society |
摘要 | Detecting and characterizing the community structure of complex network and social network is fundamental problem. Many of the proposed algorithm for detecting community based on modularity Q which fail to identify modules smaller than a scale community. In this paper, authors propose a new community detection algorithm based on genetic algorithm and modularity density (D value). We test our method on classical social networks whose community structure is already known and the results can be much easier compared with the method. Experiments show the capability of the method to successfully detect the community structure. © 2010 IEEE. |
关键词 | Complex networks Population dynamics Structural optimization Community detection Community detection algorithms Community structures Community-based D values Extremal optimization Modularity densities |
DOI | 10.1109/CASoN.2010.14 |
收录类别 | EI |
语种 | 英语 |
EI入藏号 | 20105213515852 |
EI主题词 | Genetic algorithms |
来源库 | Compendex |
分类代码 | 722 Computer Systems and Equipment - 921.5 Optimization Techniques - 971 Social Sciences |
引用统计 | 无
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文献类型 | 会议论文 |
条目标识符 | https://ir.lut.edu.cn/handle/2XXMBERH/116805 |
专题 | 兰州理工大学 |
作者单位 | 1.College of Electrical and Information Engineering, Lanzhou University of Technology, Lanzhou, China; 2.Division of System Simulation and Computer Application, Taiyuan University of Science and Technology, Taiyuan, China |
第一作者单位 | 兰州理工大学 |
推荐引用方式 GB/T 7714 | Liu, Jinxia,Zeng, Jianchao. Community detection based on modularity density and genetic algorithm[C]:IEEE Computer Society,2010:29-32. |
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