A community detection algorithm based on structural similarity

被引：0

作者：

Guo, Xuchao ^{[1
]}

Hao, Xia ^{[1
]}

Liu, Yaqiong ^{[1
]}

Zhang, Li ^{[1
]}

Wang, Lu ^{[1
]}

机构：

[1] Shandong Agr Univ, Coll Informat Sci & Engn, Tai An 271018, Shandong, Peoples R China

来源：

2017 2ND INTERNATIONAL SEMINAR ON ADVANCES IN MATERIALS SCIENCE AND ENGINEERING | 2017年 / 231卷

基金：

中国国家自然科学基金;

关键词：

D O I：

10.1088/1757-899X/231/1/012069

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In order to further improve the efficiency and accuracy of community detection algorithm, a new algorithm named SSTCA (the community detection algorithm based on structural similarity with threshold) is proposed. In this algorithm, the structural similarities are taken as the weights of edges, and the threshold k is considered to remove multiple edges whose weights are less than the threshold, and improve the computational efficiency. Tests were done on the Zachary's network, Dolphins' social network and Football dataset by the proposed algorithm, and compared with GN and SSNCA algorithm. The results show that the new algorithm is superior to other algorithms in accuracy for the dense networks and the operating efficiency is improved obviously.

引用

页数：8

共 15 条

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