Document (#34070)

Author

Bidoki, A.M.Z.
Yazdani, N.

Title

an intelligent ranking algorithm for web pages : DistanceRank

Source

Information processing and management. 44(2008) no.2, S.877-892

Year

2008

Abstract

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.

Theme

Retrievalalgorithmen

Object

DistanceRank

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5. Menczer, F.: Lexical and semantic clustering by Web links (2004) 0.24

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