计算机科学 ›› 2016, Vol. 43 ›› Issue (12): 153-157.doi: 10.11896/j.issn.1002-137X.2016.12.027
刘冰玉,王翠荣,王聪,苑迎
LIU Bing-yu, WANG Cui-rong, WANG Cong and YUAN Ying
摘要: 通过挖掘大数据来识别复杂社会网络上的社区,有利于对经济、政治、人口等方面的重要问题进行定量研究,社区的识别算法已经成为当前研究的热点问题。重点研究了重叠社区识别问题,提出了基于引力因子的加权复杂网络的重叠社区识别算法GWCR。该算法首先选取万有引力因子大的节点为中心节点,将节点与中心节点之间的引力因子作为衡量标准,并将节点归入社区引力因子大于某一阈值的社区,最后通过识别重叠节点来识别重叠社区。在3个真实网络数据集上的实验结果表明,与传统的重叠社区识别算法相比,GWCR算法划分的社区的模块度较高。
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