An Arnoldi-extrapolation algorithm for computing pagerank
type: Item
instance of: scholarly article
title: An Arnoldi-extrapolation algorithm for computing pagerank
zbMATH Open document ID: 1201.65059
author: Gang Wu
author: Yimin Wei
published in: Journal of Computational and Applied Mathematics
publication date: 2010-08-27T00:00:00Z
review text: The authors aim at improving the PageRank algorithm which is commonly used to determine the global importance of Web pages. The algorithm essentially needs to compute the principal eigenvector of the Google matrix and is obviously required to be very efficient. To this end, the paper proposes a new Arnoldi-Extrapolation algorithm, based on the Arnoldi-type algorithm already presented in literature. An extrapolation method based on Ritz values is developed and then conveniently introduced into the Arnoldi-type algorithm. A detailed convergence analysis is provided. Some enlightening numerical examples show the very good properties of the proposed method.
reviewed by: Raffaella Pavani
Mathematics Subject Classification ID: 65F15
Mathematics Subject Classification ID: 65F10
Mathematics Subject Classification ID: 68P10
zbMATH DE Number: 5775757
zbMATH Keywords: PageRank
zbMATH Keywords: GeneRank
zbMATH Keywords: Krylov subspace method
zbMATH Keywords: Arnoldi method
zbMATH Keywords: algorithm
zbMATH Keywords: eigenvector
zbMATH Keywords: Google matrix
zbMATH Keywords: extrapolation method
zbMATH Keywords: Ritz values
zbMATH Keywords: convergence
zbMATH Keywords: numerical examples
describes a project that uses: JDQZ
describes a project that uses: JDQR
describes a project that uses: GeneRank
MaRDI profile type: Publication
full work available at URL: j.cam.2010.02.009
OpenAlex ID: W1989699650
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DOI: 10.1016/J.CAM.2010.02.009
description: scientific article; zbMATH DE number 5775757