4.7 Article

Approximating web communities using subspace decomposition

期刊

KNOWLEDGE-BASED SYSTEMS
卷 70, 期 -, 页码 118-127

出版社

ELSEVIER
DOI: 10.1016/j.knosys.2014.06.017

关键词

Web communities; Web graphs; Subspace decomposition; Information retrieval; Community detection; Spam detection

资金

  1. National Natural Science Foundation of China [61370145, 61173183, 60973152]
  2. Doctoral Program Foundation of Institution of Higher Education of China [20070141014]
  3. Program for Liaoning Excellent Talents in University [LR2012003]
  4. National Natural Science Foundation of Liaoning Province [20082165]
  5. Fundamental Research Funds for the Central Universities [DUT12JB06]

向作者/读者索取更多资源

Herein, we propose an algorithm to approximate web communities from the topic related web pages. The approximation is achieved by subspace factorization of the topic related web pages. The factorization process reveals existing association between web pages such that the closely related web pages are extracted. We vary the approximation values to identify varied degrees of relationship between web pages. Experiments on real data sets show that the proposed algorithm reduces the impact of unrelated links and therefore can be used to control spam links in web pages. (C) 2014 Elsevier B.V. All rights reserved.

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