Detecting Community Structure by Network Vectorization

  • Wei Ren
  • Guiying Yan
  • Guohui Lin
  • Caifeng Du
  • Xiaofeng Han
Part of the Lecture Notes in Computer Science book series (LNCS, volume 5092)


With the growing number of available social and biological networks, the problem of detecting network community structure is becoming more and more important which acts as the first step to analyze these data. In this paper, we transform network data so that each node is represented by a vector, our method can handle directed and weighted networks. it also can detect networks which contain communities with different sizes and degree sequences. This paper reveals that network community can be formulated as a cluster problem.


Community Structure Adjacent Matrix Community Detection Node Pair Latent Semantic Analysis 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2008

Authors and Affiliations

  • Wei Ren
    • 1
  • Guiying Yan
    • 1
  • Guohui Lin
    • 2
  • Caifeng Du
    • 3
  • Xiaofeng Han
    • 4
  1. 1.Academy of Mathematics and Systems ScienceChinese Academy of Science 
  2. 2.Department of Computing ScienceUniversity of Alberta 
  3. 3.College of Mathematics and Computational ScienceChina University of Petroleum 
  4. 4.College of ScienceShandong University of Science and Technology 

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