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Use Noisy Link Analysis to Improve Web Search

by: Yitong Wang, and Jingbo Chu

In: HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia New York, NY, USA: ACM (July 2009) .

Abstract

Link-based ranking algorithm is very important for current success and popular of Web Search Engine. In order to get high rank, some try to improve contents of web pages while others just put dirty tricks, such as link spam. Link spam is a trick targeting at link-based ranking algorithms by artificially created tight link structures to push some target pages get undeserved high ranks. This problem becomes even worse with the advent of wikis, blogs, forums, which are rich in links. We tackle the problem of improving link-based ranking by more fundamental viewpoint--noisy link analysis. Motivated by how non-voting hyperlinks affect quality of ranking, we propose an approach and corresponding penalty strategies to both detect and handle noisy link effectively and automatically. We also compared our approach with other related works to demonstrate that our approach is rather effective in noisy link filtering and could improve the final search results significantly.

BibTeX record

@inproceedings{wang2009noisy,
  abstract = {Link-based ranking algorithm is very important for current success and popular of Web Search Engine. In order to get high rank, some try to improve contents of web pages while others just put dirty tricks, such as link spam. Link spam is a trick targeting at link-based ranking algorithms by artificially created tight link structures to push some target pages get undeserved high ranks. This problem becomes even worse with the advent of wikis, blogs, forums, which are rich in links. We tackle the problem of improving link-based ranking by more fundamental viewpoint--noisy link analysis. Motivated by how non-voting hyperlinks affect quality of ranking, we propose an approach and corresponding penalty strategies to both detect and handle noisy link effectively and automatically. We also compared our approach with other related works to demonstrate that our approach is rather effective in noisy link filtering and could improve the final search results significantly.},
  added-at = {2009-06-16T15:00:02.000+0200},
  address = {New York, NY, USA},
  author = {Wang, Yitong and Chu, Jingbo},
  biburl = {http://www.bibsonomy.org/bibtex/2d052e05bf9f05fed6d21bb72443e4cf0/ht09},
  booktitle = {HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia},
  interhash = {2ec22f9855dd1fb454c12f9df837bfb3},
  intrahash = {d052e05bf9f05fed6d21bb72443e4cf0},
  keywords = {ht2009 link link-based noisy pagerank penalty poster pp162 ranking},
  month = {July},
  paperid = {pp162},
  publisher = {ACM},
  session = {Poster},
  timestamp = {2009-06-16T15:00:02.000+0200},
  title = {Use Noisy Link Analysis to Improve Web Search},
  year = 2009
}

Endnote record

%0 Conference Paper
%1 wang2009noisy
%A Wang, Yitong
%A Chu, Jingbo
%B HT '09: Proceedings of the Twentieth ACM Conference on Hypertext and Hypermedia
%C New York, NY, USA
%D 2009
%I ACM
%K 
%T Use Noisy Link Analysis to Improve Web Search
%X Link-based ranking algorithm is very important for current success and popular of Web Search Engine. In order to get high rank, some try to improve contents of web pages while others just put dirty tricks, such as link spam. Link spam is a trick targeting at link-based ranking algorithms by artificially created tight link structures to push some target pages get undeserved high ranks. This problem becomes even worse with the advent of wikis, blogs, forums, which are rich in links. We tackle the problem of improving link-based ranking by more fundamental viewpoint--noisy link analysis. Motivated by how non-voting hyperlinks affect quality of ranking, we propose an approach and corresponding penalty strategies to both detect and handle noisy link effectively and automatically. We also compared our approach with other related works to demonstrate that our approach is rather effective in noisy link filtering and could improve the final search results significantly.