计算机科学 ›› 2022, Vol. 49 ›› Issue (11A): 210800144-11.doi: 10.11896/jsjkx.210800144
潘雨1,2, 王帅辉3, 张磊1, 胡谷雨1, 邹军华1, 王田丰1, 潘志松1
PAN Yu1,2, WANG Shuai-hui3, ZHANG Lei1, HU Gu-yu1, ZOU Jun-hua1, WANG Tian-feng1, PAN Zhi-song1
摘要： 在复杂网络中,社团结构是广泛存在的重要潜在结构。挖掘复杂网络中的社团结构,对探索网络潜在特性、理解网络组织结构、发现网络隐藏规律和交互模式等具有重要的理论和现实意义,是网络分析任务的关键研究内容。介绍了社团发现的背景和意义,并从静态网络社团发现和动态网络社团发现两个方面对社团发现的方法进行了总结和梳理。其中,静态网络的社团发现包括基于划分的社团发现方法、基于层次聚类的社团发现方法、基于模块度的社团发现方法、基于非负矩阵分解的社团发现方法和基于深度学习的社团发现方法。动态网络社团发现包括增量聚类的社团发现方法和演化聚类的社团发现方法。另外介绍了常用的社团发现评价指标,并在最后讨论了社团发现所面临的一些挑战及未来的发展方向。
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