Page 174 - 《软件学报》2020年第11期

3490 Journal of Software 软件学报 Vol.31, No.11, November 2020

现方法由于难以获取其全局结构,无法有效处理这些动态的大型复杂网络.因此,近些年,局部社区发现算法引
起了广大学者的关注.针对复杂社会网络中个体间的相似关系是模糊的或不确定的,本文提出一种基于模糊相
似关系的局部社区发现方法.首先,采用模糊关系来刻画一条边的两个节点之间的相似关系.然后证明了该模糊
关系为模糊相似关系,将某一节点所在的社区转化为节点关于模糊相似关系 q 水平上的等价类,通过寻找最大
连通子图方法得到某一节点所在的局部社区.与其他算法相比,本文算法在仿真网络数据集和真实网络数据集
上都取得了良好的效果.此外,还观察了参数 q 的变化对本文算法的影响,给参数设置提供了依据.
为了适应社会媒体和社交网络快速发展的需要,我们下一步的工作将针对动态的、异构的、内容与链接结
合的复杂大型真实社会网络,设计出快速、高准确度和无监督的局部社区发现算法.

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