Detecting Overlapping Communities of Weighted Networks by Central Figure Algorithm

被引：0

作者：

Tong, Chao ^{[1
]}

Xie, Zhongyu ^{[1
]}

Mo, Xiaoyun ^{[1
]}

Niu, Jianwei ^{[1
]}

Zhang, Yan ^{[2
]}

机构：

[1] Beihang Univ, Sch Comp Sci & Engn, Beijing, Peoples R China

[2] China Univ Petr, Coll Geophys & Informat Engn, Beijing, Peoples R China

来源：

2014 IEEE COMPUTING, COMMUNICATIONS AND IT APPLICATIONS CONFERENCE (COMCOMAP) | 2014年

关键词：

weighted networks; overlapping community; central figure; triadic closure; SMALL-WORLD NETWORKS;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

In recent years, the community structures in complex networks has become a research hotspot. In this paper, we focus on weighted networks and propose a unique algorithm on detecting overlapping communities of weighted networks based on central figure with considerable accuracy. In the algorithm, all the central figures are first extracted. Then to each central figure, nodes are absorbed by closures and weak ties. The experiments are based on LFR Benchmark. Through the experiment, we can know that the performance of our algorithm is better than that of COPRA (Community Overlap Propagation Algorithm) algorithm.

引用

页码：7 / 12

页数：6

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