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The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Page quality: in search of an unbiased web ranking

Cho, Junghoo, Roy, Sourashis, Adams, Robert E.·2005·Proceedings of the 2005 ACM SIGMOD international conference on Management of data
DOI 10.1145/1066157.1066220
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Abstract

In a number of recent studies [4, 8] researchers have found that because search engines repeatedly return currently popular pages at the top of search results, popular pages tend to get even more popular, while unpopular pages get ignored by an average user. This "rich-get-richer" phenomenon is particularly problematic for new and high-quality pages because they may never get a chance to get users' attention, decreasing the overall quality of search results in the long run. In this paper, we propose a new ranking function, called page quality that can alleviate the problem of popularity-based ranking. We first present a formal framework to study the search engine bias by discussing what is an "ideal" way to measure the intrinsic quality of a page. We then compare how PageRank, the current ranking metric used by major search engines, differs from this ideal quality metric. This framework will help us investigate the search engine bias in more concrete terms and provide clear understanding why PageRank is effective in many cases and exactly when it is problematic. We then propose a practical way to estimate the intrinsic page quality to avoid the inherent bias of PageRank. We derive our proposed quality estimator through a careful analysis of a reasonable web user model, and we present experimental results that show the potential of our proposed estimator. We believe that our quality estimator has the potential to alleviate the rich-get-richer phenomenon and help new and high-q…

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Citations

Cites

Research works printed but not linked: 29

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Metadata

Authors
Cho, J., Roy, S., & Adams, R. E.
Affiliations
UCLA Computer Science
Venue
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Publisher
ACM
Published
2005-06-14
Pages
551-562
DOI
10.1145/1066157.1066220
Cited by
69
References
1
Licence
www.acm.org/publications/policies/copyright_policy#Background (vor)

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