FLPA: A fast label propagation algorithm for detecting overlapping community structure

被引:4
|
作者
Yan, Rong
Yuan, Wei
Su, Xiangdong [1 ]
Zhang, Ziyi
机构
[1] Inner Mongolia Univ, Coll Comp Sci, Hohhot, Peoples R China
基金
中国国家自然科学基金;
关键词
Complex network; Community detection; Label propagation algorithm; Overlapping community detection; COMPLEX NETWORKS; FUZZY;
D O I
10.1016/j.eswa.2023.120971
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In complex networks, there are a huge number of overlapping community structures, and those structures have been an increasing concern in recent years. The label propagation algorithm (LPA) family is a kind of mainstream method that discovers different community structures in complex networks. But these methods often struggle with stability and feasibility, as well as issues sensitive to network size. In this paper, to solve the above problems and improve the detection accuracy, we present a fast label propagation algorithm (FLPA) based on node influence and label weight. In FLPA, we first use the graph compression technique to reduce the network size. Then, we propose a new node influence calculation method and fuse it with the ������-path similarity to precisely control the label weight in the label propagation stage. Through the above process, FLPA makes the labels that are propagated and received by nodes more reasonable and further improves the detection accuracy. Finally, we restore the network and make the compressed node belong to the same community as its corresponding super node. Experimental results on 10 real and 58 synthetic networks indicate that FLPA is suitable for detecting overlapping community structures regardless of network scale and accomplishes better than state-of-the-art methods on stability and feasibility.
引用
收藏
页数:13
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