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Received: 2008-06-23

Revision Accepted: 2008-11-04

Crosschecked: 2009-06-10

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Journal of Zhejiang University SCIENCE A 2009 Vol.10 No.8 P.1114~1124

http://doi.org/10.1631/jzus.A0820481


On-line topical importance estimation: an effective focused crawling algorithm combining link and content analysis


Author(s):  Can WANG, Zi-yu GUAN, Chun CHEN, Jia-jun BU, Jun-feng WANG, Huai-zhong LIN

Affiliation(s):  School of Computer Science and Technology, Zhejiang University, Hangzhou 310027, China

Corresponding email(s):   wcan@zju.edu.cn

Key Words:  Focused crawlers, Topical crawlers, PageRank, Classifiers, On-line topical importance estimation (OTIE) algorithm


Can WANG, Zi-yu GUAN, Chun CHEN, Jia-jun BU, Jun-feng WANG, Huai-zhong LIN. On-line topical importance estimation: an effective focused crawling algorithm combining link and content analysis[J]. Journal of Zhejiang University Science A, 2009, 10(8): 1114~1124.

@article{title="On-line topical importance estimation: an effective focused crawling algorithm combining link and content analysis",
author="Can WANG, Zi-yu GUAN, Chun CHEN, Jia-jun BU, Jun-feng WANG, Huai-zhong LIN",
journal="Journal of Zhejiang University Science A",
volume="10",
number="8",
pages="1114~1124",
year="2009",
publisher="Zhejiang University Press & Springer",
doi="10.1631/jzus.A0820481"
}

%0 Journal Article
%T On-line topical importance estimation: an effective focused crawling algorithm combining link and content analysis
%A Can WANG
%A Zi-yu GUAN
%A Chun CHEN
%A Jia-jun BU
%A Jun-feng WANG
%A Huai-zhong LIN
%J Journal of Zhejiang University SCIENCE A
%V 10
%N 8
%P 1114~1124
%@ 1673-565X
%D 2009
%I Zhejiang University Press & Springer
%DOI 10.1631/jzus.A0820481

TY - JOUR
T1 - On-line topical importance estimation: an effective focused crawling algorithm combining link and content analysis
A1 - Can WANG
A1 - Zi-yu GUAN
A1 - Chun CHEN
A1 - Jia-jun BU
A1 - Jun-feng WANG
A1 - Huai-zhong LIN
J0 - Journal of Zhejiang University Science A
VL - 10
IS - 8
SP - 1114
EP - 1124
%@ 1673-565X
Y1 - 2009
PB - Zhejiang University Press & Springer
ER -
DOI - 10.1631/jzus.A0820481


Abstract: 
Focused crawling is an important technique for topical resource discovery on the Web. The key issue in focused crawling is to prioritize uncrawled uniform resource locators (URLs) in the frontier to focus the crawling on relevant pages. Traditional focused crawlers mainly rely on content analysis. Link-based techniques are not effectively exploited despite their usefulness. In this paper, we propose a new frontier prioritizing algorithm, namely the on-line topical importance estimation (OTIE) algorithm. OTIE combines link- and content-based analysis to evaluate the priority of an uncrawled URL in the frontier. We performed real crawling experiments over 30 topics selected from the Open Directory Project (ODP) and compared harvest rate and target recall of the four crawling algorithms: breadth-first, link-context-prediction, on-line page importance computation (OPIC) and our OTIE. Experimental results showed that OTIE significantly outperforms the other three algorithms on the average target recall while maintaining an acceptable harvest rate. Moreover, OTIE is much faster than the traditional focused crawling algorithm.

Darkslateblue:Affiliate; Royal Blue:Author; Turquoise:Article

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