Detecting Overlapping Communities in Complex Networks: An Evolutionary Label Propagation Approach

被引:0
|
作者
Saif, Mojtaba [1 ]
Samie, Mohammad Ebrahim [2 ]
Hamzeh, Ali [1 ]
机构
[1] Shiraz Univ, CSE & IT Dept, Shiraz, Fars, Iran
[2] Jahrom Univ, Dept Comp Engn & IT, Jahrom, Fars, Iran
关键词
Complex network; label propagation algorithm; overlapping community detection; SOCIAL NETWORKS; ALGORITHM; INFORMATION; SIMILARITY;
D O I
10.1142/S0219622023500062
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
A challenging issue in complex network analysis is overlapping community detection, which has attracted many studies. Label Propagation Algorithm (LPA) is one of the famous studies to detect communities. But it has some weaknesses such as using local information and randomly choosing the sequences of processing nodes. We introduce Evolutionary Label Propagation Algorithm (ELPA) to solve these problems and improve accuracy. ELPA uses an intelligent search instead of randomly processing nodes and fuses local and global perspectives. The proposed ELPA is compared with several state-of-the-art algorithms on synthetic and real-world networks with different sizes, densities, and complexities. The results indicate that ELPA provides better results on most of the test instances. Therefore, ELPA is an accurate and efficient algorithm for detecting overlapping communities.
引用
收藏
页码:327 / 360
页数:34
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