Detecting Community Structures Within Complex Networks Using a Discrete Unconscious Search Algorithm.

International Journal of Operations Research and Information Systems(2021)

引用 0|浏览4
暂无评分
摘要
Detecting the communities that exist within complex social networks has a wide range of application in business, engineering, and sociopolitical settings. As a result, many community detection methods are being developed by researchers in the academic community. If the communities within social networks can be more accurately detected, the behavior or characteristics of each community within the networks can be better understood, which implies that better decisions can be made. In this paper, a discrete version of an unconscious search algorithm was applied to three widely explored complex networks. After these networks were formulated as optimization problems, the unconscious search algorithm was applied, and the results were compared against the results found from a comprehensive review of state-of-the-art community detection methods. The comparative study shows that the unconscious search algorithm consistently produced the highest modularity that was discovered through the comprehensive review of the literature.
更多
查看译文
关键词
Evolutionary Searched-Based Algorithms,Modularity,Social Networks,Unweighted and Undirected Networks
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要