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Available viahttp://dbpubs.stanford.edu/pub/2003-45
Submitted on 16th of July 2003
Author Haveliwala, Taher; Kamvar, Sepandar; Klein, Dan; Manning, Chris; Golub, Gene
Title Computing PageRank using Power Extrapolation
Date of publication 2003
Published in Stanford University Technical Report
Citation Haveliwala, Taher; Kamvar, Sepandar; Klein, Dan; Manning, Chris; Golub, Gene. Computing PageRank using Power Extrapolation, Stanford University Technical Report, 2003.
Number of pages 12
Language English
Project Stanford InfoLab; Database Group; Natural Language Processing Group
Type Technical Report
Subject group Computer Science; Databases and the Web; Miscellaneous
Abstract We present a novel technique for speeding up the computation of PageRank, a hyperlink-based estimate of the ``importance'' of Web pages, based on the ideas presented in "Extrapolation Methods for Accelerating PageRank Computations". The original PageRank algorithm uses the Power Method to compute successive iterates that converge to the principal eigenvector of the Markov matrix representing the Web link graph. The algorithm presented here, called Power Extrapolation, accelerates the convergence of the Power Method by subtracting off the error along several nonprincipal eigenvectors from the current iterate of the Power Method, making use of known nonprincipal eigenvalues of the Web hyperlink matrix. Empirically, we show that using Power Extrapolation speeds up PageRank computation by 30% on a Web graph of 80 million nodes in realistic scenarios over the standard power method, in a way that is simple to understand and implement.
Keywords PageRank, link analysis, search
Contact address taherh@stanford.edu
sdkamvar@stanford.edu
klein@cs.stanford.edu
Sponsored by This paper is based on work supported in part by the National
Science Foundation under Grants No.\ IIS-0085896 and CCR-9971010, and
in part by the Research Collaboration
between NTT Communication Science Laboratories, Nippon Telegraph and
Telephone Corporation and CSLI, Stanford University (research project
on Concept Bases for Lexical Acquisition and Intelligently Reasoning
with Meaning).
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