计算机与现代化 ›› 2013, Vol. 1 ›› Issue (5): 231-234.doi:

• 应用与开发 • 上一篇    下一篇

复杂网络中基于节点相似性聚类的网络社团发现方法研究

郑凤妮   

  1. 华南理工大学计算机科学与工程学院,广东广州510006
  • 收稿日期:2012-12-28 修回日期:1900-01-01 出版日期:2013-05-28 发布日期:2013-05-28

Research on Network Community-finding Method on Complex Network Based on Similar Network Node Clustering

ZHENG Feng-ni   

  1. School of Computer Science & Engineering, South China University of Technology, Guangzhou 510006, China
  • Received:2012-12-28 Revised:1900-01-01 Online:2013-05-28 Published:2013-05-28

摘要: 针对复杂网络社团发现的问题,使用聚类方法对其进行详细的研究,将网络节点的数据结构转化成聚类算法的数据结构,根据节点之间的相似度对节点进行合并或分割,并且使用向量计算的方法对复杂网络的节点相似度进行度量。改进的算法把网络中的每个节点都作为一个信息源,具有收发信息的功能,按照改进的信息传递方法进行相似度值的传递和遍历,使用复杂网络中常用的Zachary俱乐部网络作为实验对象验证。本方法提高了复杂网络社团发现的算法效率。

关键词: 社团发现, 聚类算法, 节点相似性, 节点向量化

Abstract: According to the problems of community-finding on complex networks, this paper detailed studies the clustering method to it, changes the data structure of the network node into that of clustering algorithm, amalgamating or partitioning nodes according to the similarity of nodes, and uses the vector method to measure the similarity of complex network nodes. The improved algorithm makes each node on network as a source having sending and receiving messages function, transfers and traverses similarity value according to the improved information transmission method, uses Karate club network commonly uses on complex network as verification of the experimental object. It improves the efficiency of community-finding on complex networks.

Key words: community-finding, clustering algorithm, similarity between nodes, node quantifying

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