March 28, 2024, 4:43 a.m. | Jiakang Li, Songning Lai, Zhihao Shuai, Yuan Tan, Yifan Jia, Mianyang Yu, Zichen Song, Xiaokang Peng, Ziyang Xu, Yongxin Ni, Haifeng Qiu, Jiayu Yang,

cs.LG updates on arXiv.org arxiv.org

arXiv:2309.11798v3 Announce Type: replace-cross
Abstract: The study of complex networks has significantly advanced our understanding of community structures which serves as a crucial feature of real-world graphs. Detecting communities in graphs is a challenging problem with applications in sociology, biology, and computer science. Despite the efforts of an interdisciplinary community of scientists, a satisfactory solution to this problem has not yet been achieved. This review article delves into the topic of community detection in graphs, which serves as a thorough …

abstract advanced applications arxiv biology communities community computer computer science cs.lg cs.si detection feature graphs networks review science scientists sociology study type understanding world

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