Page-reRank: using trusted links to re-rank authority
Paolo Massa
In Book "Search Engines", IFCAI University Press.
This work is licensed under a Creative Commons Attribution-Share Alike 3.0 License.
2007
The paper is released under Creative Commons! Creative Commons License
Page-reRank: Using Trust to Re-Rank Authority
Page-reRank: Using Trust to Re-Rank Authority

Page-reRank: using trusted links to re-rank authority

Abstract
The basis of much of the intelligence on the Web is the hyperlink structure which represents an organising principle based on the human facility to be able to discriminate between relevant and irrelevant material. Second generation search engines like Google make use of this structure to infer the authority of particular web pages. However, the linking mechanism provided by HTML does not allow the author to express different types of links such as positive or negative endorsements of page content. Consequently, algorithms like PageRank produce rankings that do not capture the different intentions of web authors. In this paper, we review some of the initiatives for adding simple semantic extensions to the link mechanism. Using a large real world dataset, we demonstrate the different page rankings produced by considering extra semantic information in page links. We conclude that Web intelligence would benefit in adoption of languages that allow authors to easily encode simple semantic extensions to their hyperlinks.

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