Survey of community detection algorithms in complex network

Li Hui
Chen Fucai
Zhang Jianpeng
Wu Zheng
Li Shaomei
Huang Ruiyang
Information Engineering University, Zhengzhou 450002, China

Abstract

The community detection method can mine hidden cluster structure in the network, which is of great significance for the analysis of the structure and function of complex network. In recent years, with the explosive growth of network data and the diversity of network evolution, a large number of methods and frameworks for community detection that can handle different scenarios have emerged. In order to deeply understand the research status and development trend, this paper reviewed the community detection methods. This paper firstly classified these algorithms, introduced each kind of algorithm in detail and made analysis and comparison, and then introduced some commonly used evaluation indicators and expounded the application scenarios. Finally, this paper looked forward to the future research directions of this field.

Foundation Support

国家自然科学基金群体项目
国家重点研发计划项目
郑州市协同创新重大专项资助项目

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0211
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Survey
Pages: 1611-1618
Serial Number: 1001-3695(2021)06-002-1611-08

Publish History

[2021-06-05] Printed Article

Cite This Article

李辉, 陈福才, 张建朋, 等. 复杂网络中的社团发现算法综述 [J]. 计算机应用研究, 2021, 38 (6): 1611-1618. (Li Hui, Chen Fucai, Zhang Jianpeng, et al. Survey of community detection algorithms in complex network [J]. Application Research of Computers, 2021, 38 (6): 1611-1618. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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