基于路径相似度的社区检测方法

Community Detection Based on Path Similarity

本文提出一种基于相似度的复杂网络社区检测算法。在原有Kuramoto振荡器相位同步的基础上,为了使两个连接振荡器的相位同步,两个不相连振荡器的相位异步,加入了基于路径的相似度计算函数。节点的不同邻居有不同的亲密关系,有亲密关系的节点更有可能在一个社区,而节点的相似度就是描述他们之间的亲密程度。在这种改进模型的基础上,整个网络会分为几个相位值不同的同步簇。为了验证算法的性能,本文针对空手道网络,海豚网络进行了仿真并与已有文献作相关比较取得一定的优势。

A complex network community detection method based on similarity is proposed.Different neighbors have different intimate relationship,which means intimate nodes are more likely in a community.Then similarity of nodes is adopted to describe their intimate.In order to make the two connected oscillators cluster together and two unconnected oscillators get away,similarity based on path is adopted to Kuramoto model.Nodes in the networks will be divided into different synchronization cluster based on this improved model.Karate network and dolphin network are tested to verify the performance of the proposed algorithm.Several simulations results show our proposed method is more efficient.