Finding Related Pages Using the Link Structure of the WWW

Abstract

Most of the current algorithms for finding related pages are exclusively based on text corpora of the WWW or incorporate only authority or hub values of pages. In this paper, we present HubFinder, a new fast algorithm for finding related pages exploring the link structure of the Web graph. Its criterion for filtering output pages is pluggable, depending on the user's interests, and may vary from global page ranks to text content, etc. We also introduce HubRank, a new ranking algorithm which gives a more complete view of page importance by biasing the authority measure of PageRank towards hub values of pages. Finally, we present an evaluation of these algorithms in order to prove their qualities experimentally.