An important problem in Web search is to determine the importance of each page. This problem consists in computing, by the power method, the left principal eigenvector (the PageRank vector) of a matrix depending on a parameter $c$ which has to be chosen close to 1. However, when $c$ is close to 1, the problem is ill-conditioned, and the power method converges slowly. So, the idea developed in this paper consists in computing the PageRank vector for several values of $c$, and then to extrapolate them, by a conveniently chosen rational function, at a point near 1. The choice of this extrapolating function is based on the mathematical considerations about the PageRank vector.

Extrapolation and minimization procedures for the PageRank vector

REDIVO ZAGLIA, MICHELA
2007

Abstract

An important problem in Web search is to determine the importance of each page. This problem consists in computing, by the power method, the left principal eigenvector (the PageRank vector) of a matrix depending on a parameter $c$ which has to be chosen close to 1. However, when $c$ is close to 1, the problem is ill-conditioned, and the power method converges slowly. So, the idea developed in this paper consists in computing the PageRank vector for several values of $c$, and then to extrapolate them, by a conveniently chosen rational function, at a point near 1. The choice of this extrapolating function is based on the mathematical considerations about the PageRank vector.
2007
Web Information Retrieval and Linear Algebra Algorithms
Seminar 07071 - Web Information Retrieval and Linear Algebra Algorithms
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/1780695
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