Community Structure Detection Using Firefly Algorithm

被引:10
作者
Jaradat, Ameera Saleh [1 ]
Hamad, Safa'a Bani [2 ]
机构
[1] Yarmouk Univ, Comp Sci Dept, Irbid, Jordan
[2] Yarmouk Univ, Irbid, Jordan
关键词
Algorithms; Community Detection; Complex Networks; Heuristic Algorithm; Optimization;
D O I
10.4018/IJAMC.2018100103
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This article describes how parallel to the continuous growth of the Internet, which allows people to share and collaborate more, social networks have become more attractive as a research topic in many different disciplines. Community structures are established upon interactions between people. Detection of these communities has become a popular topic in computer science. How to detect the communities is of great importance for understanding the organization and function of networks. Community detection is considered a variant of the graph partitioning problem which is NP-hard. In this article, the Firefly algorithm is used as an optimization algorithm to solve the community detection problem by maximizing the modularity measure. Firefly algorithm is a new Nature-inspired heuristic algorithm that proved its good performance in a variety of applications. Experimental results obtained from tests on real-life networks demonstrate that the authors' algorithm successfully detects the community structure.
引用
收藏
页码:52 / 70
页数:19
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