Extrapolation methods for PageRank computations

被引:28
|
作者
Brezinski, C [1 ]
Redivo-Zaglia, M
Serra-Capizzano, S
机构
[1] Univ Sci & Tech Lille, UFR Math Pures & Appl, CNRS, UMR 8524,Lab Paul Painleve, F-59655 Villeneuve Dascq, France
[2] Univ Padua, Dipartimento Matemat Pura & Applicata, I-35131 Padua, Italy
[3] Univ Insubria, Dipartimento Matemat & Fis, I-22100 Como, Italy
关键词
D O I
10.1016/j.crma.2005.01.015
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The mathematical problem behind Web search is the computation of the nonnegative left eigenvector of a stochastic matrix P corresponding to the dominant eigenvalue 1. This vector is called the PAGERANK vector. Since the matrix P is ill-conditioned, the computation of PAGERANK is difficult and the matrix P is replaced by P(c) = cP + (1 - c)E, where E is a rank one matrix and c a parameter. The dominant left eigenvector of P(c) is denoted by PAGERANK(c). This vector can be computed for several values of c and then extrapolated at the point c = 1. In this Note, we construct special extrapolation methods for this problem. They are based on the mathematical analysis of the vector PAGERANK(c).
引用
收藏
页码:393 / 397
页数:5
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