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
- National Natural Science Foundation of China [61370145, 61173183, 60973152]
- Doctoral Program Foundation of Institution of Higher Education of China [20070141014]
- Program for Liaoning Excellent Talents in University [LR2012003]
- National Natural Science Foundation of Liaoning Province [20082165]
- Fundamental Research Funds for the Central Universities [DUT12JB06]
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.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据