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Implicit link analysis for small web search

by: Gui-Rong Xue, Hua-Jun Zeng, Zheng Chen, Wei-Ying Ma, Hong-Jiang Zhang, and Chao-Jun Lu

In: SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval New York, NY, USA: ACM (2003) , p. 56--63.

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URL:	http://dx.doi.org/10.1145/860435.860448
DOI:	10.1145/860435.860448

Current Web search engines generally impose link analysis-based re-ranking on web-page retrieval. However, the same techniques, when applied directly to small web search such as intranet and site search, cannot achieve the same performance because their link structures are different from the global Web. In this paper, we propose an approach to constructing implicit links by mining users' access patterns, and then apply a modified PageRank algorithm to re-rank web-pages for small web search. Our experimental results indicate that the proposed method outperforms content-based method by 16\%, explicit link-based PageRank by 20\% and DirectHit by 14\%, respectively

BibTeX record

@inproceedings{citeulike:1826402,
  abstract = {Current Web search engines generally impose link analysis-based re-ranking on web-page retrieval. However, the same techniques, when applied directly to small web search such as intranet and site search, cannot achieve the same performance because their link structures are different from the global Web. In this paper, we propose an approach to constructing implicit links by mining users' access patterns, and then apply a modified PageRank algorithm to re-rank web-pages for small web search. Our experimental results indicate that the proposed method outperforms content-based method by 16\%, explicit link-based PageRank by 20\% and DirectHit by 14\%, respectively},
  added-at = {2009-07-01T11:12:30.000+0200},
  address = {New York, NY, USA},
  author = {Xue, Gui-Rong and Zeng, Hua-Jun and Chen, Zheng and Ma, Wei-Ying and Zhang, Hong-Jiang and Lu, Chao-Jun},
  biburl = {http://www.bibsonomy.org/bibtex/20a0b5336633c7b3cca0de87938d8add3/brusilovsky},
  booktitle = {SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval},
  citeulike-article-id = {1826402},
  doi = {10.1145/860435.860448},
  interhash = {992adcf8c73cb58c085773e0013bf848},
  intrahash = {0a0b5336633c7b3cca0de87938d8add3},
  isbn = {1581136463},
  keywords = {datamining en social-search www-search},
  pages = {56--63},
  posted-at = {2007-10-26 20:12:12},
  priority = {2},
  publisher = {ACM},
  timestamp = {2009-07-01T11:12:30.000+0200},
  title = {Implicit link analysis for small web search},
  url = {http://dx.doi.org/10.1145/860435.860448},
  year = 2003
}

Endnote record

%0 Conference Paper
%1 citeulike:1826402
%A Xue, Gui-Rong
%A Zeng, Hua-Jun
%A Chen, Zheng
%A Ma, Wei-Ying
%A Zhang, Hong-Jiang
%A Lu, Chao-Jun
%B SIGIR '03: Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
%@ 1581136463
%C New York, NY, USA
%D 2003
%I ACM
%K 
%P 56--63
%T Implicit link analysis for small web search
%R 10.1145/860435.860448
%U http://dx.doi.org/10.1145/860435.860448
%X Current Web search engines generally impose link analysis-based re-ranking on web-page retrieval. However, the same techniques, when applied directly to small web search such as intranet and site search, cannot achieve the same performance because their link structures are different from the global Web. In this paper, we propose an approach to constructing implicit links by mining users' access patterns, and then apply a modified PageRank algorithm to re-rank web-pages for small web search. Our experimental results indicate that the proposed method outperforms content-based method by 16\%, explicit link-based PageRank by 20\% and DirectHit by 14\%, respectively

BibSonomy :: publication ::

Implicit link analysis for small web search

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Abstract

BibTeX record

Endnote record