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2008

DistanceRank: An intelligent ranking algorithm for web pages

8 years 9 months ago
DistanceRank: An intelligent ranking algorithm for web pages
A fast and efficient page ranking mechanism for web crawling and retrieval remains as a challenging issue. Recently, several link based ranking algorithms like PageRank, HITS and OPIC have been proposed. In this paper, we propose a novel recursive method based on reinforcement learning which considers distance between pages as punishment, called ``DistanceRank'' to compute ranks of web pages. The distance is defined as the number of ``average clicks'' between two pages. The objective is to minimize punishment or distance so that a page with less distance to have a higher rank. Experimental results indicate that DistanceRank outperforms other ranking algorithms in page ranking and crawling scheduling. Furthermore, the complexity of DistanceRank is low. We have used University of California at Berkeley's web for our experiments.
Ali Mohammad Zareh Bidoki, Nasser Yazdani
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2008
Where IPM
Authors Ali Mohammad Zareh Bidoki, Nasser Yazdani
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