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Available viahttp://dbpubs.stanford.edu/pub/2003-26
Submitted on 28th of April 2003
Author Kamvar, Sepandar; Haveliwala, Taher; Golub, Gene
Title Adaptive Methods for the Computation of PageRank
Date of publication 28th of April 2003
Citation Kamvar, Sepandar; Haveliwala, Taher; Golub, Gene. Adaptive Methods for the Computation of PageRank,
Number of pages 15
Language English
Project Stanford InfoLab; Database Group; Natural Language Processing Group
Type Technical Report
Subject group Databases and the Web
Abstract We observe that the convergence patterns of pages in the PageRank algorithm have a nonuniform distribution. Specifically, many pages converge to their true PageRank quickly, while relatively few pages take a much longer time to converge. Furthermore, we observe that these slow-converging pages are generally those pages with high PageRank. We use this observation to devise a simple algorithm to speed up the computation of PageRank, in which the PageRank of pages that have converged are not recomputed at each iteration after convergence. This algorithm, which we call Adaptive PageRank, speeds up the computation of PageRank by nearly 30\%.
Keywords PageRank, web search
Contact address sdkamvar@stanford.edu
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