A Note on the Eigenvalues of the Google Matrix

Fuente: arXiv
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1. Verfasser: Eldén, Lars
Format: Preprint
Veröffentlicht: 2004
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_version_ 1866912655588982784
author Eldén, Lars
author_facet Eldén, Lars
contents The Google matrix is a positive, column-stochastic matrix that is used to compute the pagerank of all the web pages on the Internet: the eigenvector corresponding to the eigenvalue 1 is the pagerank vector. Due to its huge dimension, of the order of billions, the (presently) only viable method to compute the eigenvector is the power method. For the convergence of the iteration, it is essential to know the eigenvalue distribution of the matrix. A theorem concerning the eigenvalues was recently proved by Langville and Meyer. In this note another proof is given.
format Preprint
id arxiv_https___arxiv_org_abs_math_0401177
institution arXiv
publishDate 2004
record_format arxiv
spellingShingle A Note on the Eigenvalues of the Google Matrix
Eldén, Lars
Rings and Algebras
Numerical Analysis
15A51; 15A18
The Google matrix is a positive, column-stochastic matrix that is used to compute the pagerank of all the web pages on the Internet: the eigenvector corresponding to the eigenvalue 1 is the pagerank vector. Due to its huge dimension, of the order of billions, the (presently) only viable method to compute the eigenvector is the power method. For the convergence of the iteration, it is essential to know the eigenvalue distribution of the matrix. A theorem concerning the eigenvalues was recently proved by Langville and Meyer. In this note another proof is given.
title A Note on the Eigenvalues of the Google Matrix
topic Rings and Algebras
Numerical Analysis
15A51; 15A18
url https://arxiv.org/abs/math/0401177