计算机科学 ›› 2020, Vol. 47 ›› Issue (11A): 449-453.doi: 10.11896/jsjkx.200200049
王帅辉1,2, 胡谷雨3, 潘雨1, 张志越2, 张海峰2, 潘志松3
WANG Shuai-hui1,2, HU Gu-yu3, PAN Yu1, ZHANG Zhi-yue2, ZHANG Hai-feng2, PAN Zhi-song3
摘要： 社团结构作为复杂网络的中尺度特征,对于深入理解网络的结构和属性具有重要的意义。与无符号网络不同,符号网络包括正边和负边,分别代表了友好和敌对的关系。在形成社团时,节点通常会选择与朋友在同一社团内,而与对手在不同的社团。基于这种思想,构建了一种用于符号网络中社团发现的博弈论模型,设计了一种社团发现算法。实验结果表明,该算法在非重叠社团和重叠社团的识别中都具有卓越的性能。另外,对算法的运行效率进行了分析,提出了一种优化方法,有效地提高了算法的运行效率。
中图分类号:
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