Community detection: Concepts, algorithms, evaluation and challenges
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Published:2023-11-15
Issue:
Volume:
Page:
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ISSN:0219-6913
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Container-title:International Journal of Wavelets, Multiresolution and Information Processing
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language:en
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Short-container-title:Int. J. Wavelets Multiresolut Inf. Process.
Author:
Qu Song1,
Yuan Guan12ORCID,
Xu Hui1ORCID,
Zhang Yanmei1ORCID,
Tang Mingqing1ORCID,
Zhu Mu3ORCID
Affiliation:
1. School of Computer Science and Technology, China University of Mining and Technology, No. 1 Daxue Road, Jiangsu 22116, P. R. China
2. Digitization of Mine, Engineering Research Center of Ministry of Education, Xuzhou 221116 Jiangsu, P. R. China
3. State Key Laboratory of NBC Protection for Civilian, Beijing 100038, P. R. China
Abstract
Recently, research on complex networks has become a hot topic. Community detection, as a main task in social network analysis, plays an important role in complex networks. In this paper, we survey and summarize the development and trend of community detection and analyze typical algorithms presented in recent years. We first discuss the algorithms from algorithmic thinking, key technology and the advantages and disadvantages. Second, evaluation metrics and datasets are introduced. Finally, some application scenarios are pointed out for the potential application in the future. It is hoped that this review will serve as the steppingstone for those interested in community detection.
Funder
National Natural Science Foundation of China
Postdoctoral Science Foundation of Jiangsu Province
Jiangsu Postdoctoral Science Foundation
Xuzhou Science and Technology Project
State Key Laboratory of NBC Protection for Civilian
Publisher
World Scientific Pub Co Pte Ltd
Subject
Applied Mathematics,Information Systems,Signal Processing