计算机科学 ›› 2018, Vol. 45 ›› Issue (1): 216-222.doi: 10.11896/j.issn.1002-137X.2018.01.038
张虎,吴永科,杨陟卓,刘全明
ZHANG Hu, WU Yong-ke, YANG Zhi-zhuo and LIU Quan-ming
摘要： 社区发现是复杂网络研究中的一项重要研究内容,基于节点相似度的凝聚方法是一种典型的社区发现方法。针对现有节点相似度计算方法中存在的不足,提出一种基于多层节点的节点相似度计算方法,该方法既可以有效地计算节点之间的相似度,又可以解决节点相似度相同时的节点合并选择问题。进一步基于这种改进的节点相似度计算方法和团体之间的连接紧密度度量准则构建社区发现模型,并在真实世界的网络上进行社区发现实验。与GN算法、Fast Newman算法和改进的标签传播算法的实验结果相比,该模型可以更加准确地找到各个社区的成员。
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