复杂网络聚类方法

Translated title of the contribution: Complex network clustering algorithms

杨博*, 刘大有, 刘际明, 金弟, Hai Bin Ma

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

105 Citations (Scopus)

Abstract

Network community structure is one of the most fundamental and important topological properties of complex networks, within which the links between nodes are very dense, but between which they are quite sparse. Network clustering algorithms which aim to discover all natural network communities from given complex networks are fundamentally important for both theoretical researches and practical applications, and can be used to analyze the topological structures, understand the functions, recognize the hidden patterns, and predict the behaviors of complex networks including social networks, biological networks, World Wide Webs and so on. This paper reviews the background, the motivation, the state of arts as well as the main issues of existing works related to discovering network communities, and tries to draw a comprehensive and clear outline for this new and active research area. This work is hopefully beneficial to the researchers from the communities of complex network analysis, data mining, intelligent Web and bioinformatics.

Translated title of the contributionComplex network clustering algorithms
Original languageChinese (Simplified)
Pages (from-to)54-66
Number of pages13
Journal软件学报
Volume20
Issue number1
DOIs
Publication statusPublished - Jan 2009

Scopus Subject Areas

  • Software

User-Defined Keywords

  • Complex network
  • Network clustering
  • Network community structure

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