Matrix computations (3rd ed.)
Matrix analysis and applied linear algebra
Matrix analysis and applied linear algebra
Templates for the solution of algebraic eigenvalue problems: a practical guide
Templates for the solution of algebraic eigenvalue problems: a practical guide
Matrix algorithms
Extrapolation methods for accelerating PageRank computations
WWW '03 Proceedings of the 12th international conference on World Wide Web
Iterative Methods for Sparse Linear Systems
Iterative Methods for Sparse Linear Systems
Convergence of Restarted Krylov Subspaces to Invariant Subspaces
SIAM Journal on Matrix Analysis and Applications
Jordan Canonical Form of the Google Matrix: A Potential Contribution to the PageRank Computation
SIAM Journal on Matrix Analysis and Applications
A Reordering for the PageRank Problem
SIAM Journal on Scientific Computing
Updating Markov Chains with an Eye on Google's PageRank
SIAM Journal on Matrix Analysis and Applications
Google's PageRank and Beyond: The Science of Search Engine Rankings
Google's PageRank and Beyond: The Science of Search Engine Rankings
The PageRank Vector: Properties, Computation, Approximation, and Acceleration
SIAM Journal on Matrix Analysis and Applications
Monte Carlo Methods in PageRank Computation: When One Iteration is Sufficient
SIAM Journal on Numerical Analysis
PageRank Computation, with Special Attention to Dangling Nodes
SIAM Journal on Matrix Analysis and Applications
Journal of Computational and Applied Mathematics
Comments on "Jordan Canonical Form of the Google Matrix"
SIAM Journal on Matrix Analysis and Applications
On computing PageRank via lumping the Google matrix
Journal of Computational and Applied Mathematics
Arnoldi versus GMRES for computing pageRank: A theoretical contribution to google's pageRank problem
ACM Transactions on Information Systems (TOIS)
Triangular and skew-symmetric splitting method for numerical solutions of Markov chains
Computers & Mathematics with Applications
Accelerating the Arnoldi-Type Algorithm for the PageRank Problem and the ProteinRank Problem
Journal of Scientific Computing
Hi-index | 7.29 |
The Arnoldi-type algorithm proposed by Golub and Greif [G. Golub, C. Greif, An Arnoldi-type algorithm for computing PageRank, BIT 46 (2006) 759-771] is a restarted Krylov subspace method for computing PageRank. However, this algorithm may not be efficient when the damping factor is high and the dimension of the search subspace is small. In this paper, we first develop an extrapolation method based on Ritz values. We then consider how to periodically knit this extrapolation method together with the Arnoldi-type algorithm. The resulting algorithm is the Arnoldi-Extrapolation algorithm. The convergence of the new algorithm is analyzed. Numerical experiments demonstrate the numerical behavior of this algorithm.