An augmented Lagrangian alternating direction method for overlapping community detection based on symmetric nonnegative matrix factorization

被引:7
|
作者
Hu, Liying [1 ,2 ]
Guo, Gongde [1 ,2 ]
机构
[1] Fujian Normal Univ, Sch Math & Informat, Fuzhou, Peoples R China
[2] Fujian Normal Univ, Digital Fujian Internet Of Things Lab Environm Mo, Fuzhou, Peoples R China
基金
中国国家自然科学基金;
关键词
Augmented Lagrangian function; Alternating direction method; Symmetric nonnegative matrix factorization; Overlapping community detection; ALGORITHMS; DUALITY;
D O I
10.1007/s13042-019-00980-z
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we present an augmented Lagrangian alternating direction algorithm for symmetric nonnegative matrix factorization. The convergence of the algorithm is also proved in detail and strictly. Then we present a modified overlapping community detection method which is based on the presented symmetric nonnegative matrix factorization algorithm. We apply the modified community detection method to several real world networks. The obtained results show the capability of our method in detecting overlapping communities, hubs and outliers. We find that our experimental results have better quality than several competing methods for identifying communities.
引用
收藏
页码:403 / 415
页数:13
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