Computer Science ›› 2017, Vol. 44 ›› Issue (Z6): 419-423.doi: 10.11896/j.issn.1002-137X.2017.6A.094

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Community Structure Detection Algorithm Based on Nodes’ Eigenvectors

LU Yi-hong, ZHANG Zhen-ning and YANG Xiong   

  • Online:2017-12-01 Published:2018-12-01

Abstract: Community structure is one of the ubiquitous and significant topology characteristics of complex network.It can help us to learn the structure and functions of a complex network.The similarity index plays a vital role in community detection but it has the shortage of high time complexity and low accuracy.In order to improve the two shortages,nodes are abstracted from a complex network into a multi-dimension data set based on the theory of information transmission in the network.Combined with the traditional clustering algorithm K-means,a new community detection algorithm was proposed.The experimental results obtained from Zachary Karate Club network,Jazz Musician network and Facebook network show that the algorithm is effective and accurate.

Key words: Complex networks,Community structure,Theory of information transmission,Eigenvector

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