A Community Detection Algorithm Based on Community Size

被引：0

作者：

Gui, Jun ^{[1
]}

Deng, Changhui ^{[1
]}

Li, Hui ^{[2
]}

Gao, Jian ^{[2
]}

机构：

[1] Dalian Ocean Univ, Coll Informat Engn, Dalian 116023, Peoples R China

[2] Dalian Maritime Univ, Informat Sci & Technol Coll, Dalian 116023, Peoples R China

来源：

2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC) | 2015年

关键词：

Complex networks; Community detection; 1Pv6; Modularity;

D O I：

暂无

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 can help us understand the structure and functions of complex networks from the view of modularity. Previous algorithms of community detection represent some defects, such as high time complexity, limitation of practical application and unsuitability for large networks. Thus an improved algorithm by CNM algorithm based on community size. CNMCS algorithm, is proposed in this article. According to the data of authoritative 1P-level IPv6 networks from Jan.2009 to Dec.2010 provided by CAIDA, CNMCS algorithm is applied to these real-world networks and compared with the performance of previous algorithm. The comparison results indicate that CNMCS algorithm represents better performance according to the analysis of divided communities and modularity.

引用

页码：663 / 667

页数：5

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