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Using ODP metadata to personalize search

by: Paul A. Chirita, Wolfgang Nejdl, Raluca Paiu, and Christian Kohlsch\&\#252;tter

In: SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval New York, NY, USA: ACM Press (2005) , p. 178--185.

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URL:	http://dx.doi.org/10.1145/1076034.1076067
DOI:	10.1145/1076034.1076067

The Open Directory Project is clearly one of the largest collaborative efforts to manually annotate web pages. This effort involves over 65,000 editors and resulted in metadata specifying topic and importance for more than 4 million web pages. Still, given that this number is just about 0.05 percent of the Web pages indexed by Google, is this effort enough to make a difference? In this paper we discuss how these metadata can be exploited to achieve high quality personalized web search. First, we address this by introducing an additional criterion for web page ranking, namely the distance between a user profile defined using ODP topics and the sets of ODP topics covered by each URL returned in regular web search. We empirically show that this enhancement yields better results than current web search using Google. Then, in the second part of the paper, we investigate the boundaries of biasing PageRank on subtopics of the ODP in order to automatically extend these metadata to the whole web.

BibTeX record

@inproceedings{citeulike:685449,
  abstract = {The Open Directory Project is clearly one of the largest collaborative efforts to manually annotate web pages. This effort involves over 65,000 editors and resulted in metadata specifying topic and importance for more than 4 million web pages. Still, given that this number is just about 0.05 percent of the Web pages indexed by Google, is this effort enough to make a difference? In this paper we discuss how these metadata can be exploited to achieve high quality personalized web search. First, we address this by introducing an additional criterion for web page ranking, namely the distance between a user profile defined using ODP topics and the sets of ODP topics covered by each URL returned in regular web search. We empirically show that this enhancement yields better results than current web search using Google. Then, in the second part of the paper, we investigate the boundaries of biasing PageRank on subtopics of the ODP in order to automatically extend these metadata to the whole web.},
  added-at = {2009-07-01T11:12:30.000+0200},
  address = {New York, NY, USA},
  author = {Chirita, Paul A. and Nejdl, Wolfgang and Paiu, Raluca and Kohlsch\&\#252;tter, Christian},
  biburl = {http://www.bibsonomy.org/bibtex/2d4785a365a67a0944b65354c76d13c87/brusilovsky},
  booktitle = {SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval},
  citeulike-article-id = {685449},
  doi = {10.1145/1076034.1076067},
  interhash = {2d1ac83898547cff44ecde5dfc2c72a4},
  intrahash = {d4785a365a67a0944b65354c76d13c87},
  isbn = {1595930345},
  keywords = {adaptive-search en ontology user-profile www-search},
  pages = {178--185},
  posted-at = {2006-06-06 01:06:51},
  priority = {2},
  publisher = {ACM Press},
  timestamp = {2009-07-01T11:12:30.000+0200},
  title = {Using ODP metadata to personalize search},
  url = {http://dx.doi.org/10.1145/1076034.1076067},
  year = 2005
}

Endnote record

%0 Conference Paper
%1 citeulike:685449
%A Chirita, Paul A.
%A Nejdl, Wolfgang
%A Paiu, Raluca
%A Kohlsch\&\#252;tter, Christian
%B SIGIR '05: Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
%@ 1595930345
%C New York, NY, USA
%D 2005
%I ACM Press
%K 
%P 178--185
%T Using ODP metadata to personalize search
%R 10.1145/1076034.1076067
%U http://dx.doi.org/10.1145/1076034.1076067
%X The Open Directory Project is clearly one of the largest collaborative efforts to manually annotate web pages. This effort involves over 65,000 editors and resulted in metadata specifying topic and importance for more than 4 million web pages. Still, given that this number is just about 0.05 percent of the Web pages indexed by Google, is this effort enough to make a difference? In this paper we discuss how these metadata can be exploited to achieve high quality personalized web search. First, we address this by introducing an additional criterion for web page ranking, namely the distance between a user profile defined using ODP topics and the sets of ODP topics covered by each URL returned in regular web search. We empirically show that this enhancement yields better results than current web search using Google. Then, in the second part of the paper, we investigate the boundaries of biasing PageRank on subtopics of the ODP in order to automatically extend these metadata to the whole web.

BibSonomy :: publication ::

Using ODP metadata to personalize search

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