【摘 要】
：
图聚类算法可以用于发现社会网络中的社区结构、蛋白质互作用网络的功能模块等,是当前复杂网络研究的热点之一。合理度量网络中节点的相似性是设计有效图聚类算法的核心问题。针对此问题,本文提出了一种基于两点间短路径的节点相似性度量方法,并在此基础上给出了一种面向复杂网络的图聚类算法(A Graph Clustering Algorithm Based on Pathsbetween Nodes in Com
【出 处】
：
第二届中国计算机学会生物信息学会议
论文部分内容阅读
图聚类算法可以用于发现社会网络中的社区结构、蛋白质互作用网络的功能模块等,是当前复杂网络研究的热点之一。合理度量网络中节点的相似性是设计有效图聚类算法的核心问题。针对此问题,本文提出了一种基于两点间短路径的节点相似性度量方法,并在此基础上给出了一种面向复杂网络的图聚类算法(A Graph Clustering Algorithm Based on Pathsbetween Nodes in Complex Networks,PGC)。
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