The k-Dense Method to Extract Communities from Complex Networks

  • Kazumi Saito
  • Takeshi Yamada
  • Kazuhiro Kazama
Part of the Studies in Computational Intelligence book series (SCI, volume 165)


To understand the structural and functional properties of large-scale complex networks, it is crucial to efficiently extract a set of cohesive subnetworks as communities. There have been proposed several such community extraction methods in the literature, including the classical k-core decomposition method and, more recently, the k-clique based community extraction method. The k-core method, although computationally efficient, is often not powerful enough for uncovering a detailed community structure and it only discovers coarse-grained and loosely connected communities. The k-clique method, on the other hand, can extract fine-grained and tightly connected communities but requires a substantial amount of computational load for large-scale complex networks. In this paper, we present a new notion of a subnetwork called k-dense, and propose an efficient algorithm for extracting k-dense communities. We applied our method to the three different types of networks assembled from real data, namely, from blog trackbacks, word associations and Wikipedia references, and demonstrated that the k-dense method could extract communities almost as efficiently as the k-core method, while the qualities of the extracted communities are comparable to those obtained by the k-clique method.


Adjacent Node Word Association Community Size Maximum Community Strong Positive Relation 
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 2009

Authors and Affiliations

  • Kazumi Saito
    • 1
  • Takeshi Yamada
    • 2
  • Kazuhiro Kazama
    • 3
  1. 1.School of Administration and InformaticsUniversity of ShizuokaShizuokaJapan
  2. 2.NTT Communication Science Laboratories, NTT CorporationKyotoJapan
  3. 3.NTT Network Innovation Laboratories, NTT CorporationTokyoJapan

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