Comparison of Krylov subspace methods on the PageRank problem
Journal of Computational and Applied Mathematics
Journal of Computational and Applied Mathematics
On computing PageRank via lumping the Google matrix
Journal of Computational and Applied Mathematics
PageRank: Functional dependencies
ACM Transactions on Information Systems (TOIS)
The general extrapolation formula for acceleration PageRank computations
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 7
Google PageRanking problem: The model and the analysis
Journal of Computational and Applied Mathematics
An Arnoldi-Extrapolation algorithm for computing PageRank
Journal of Computational and Applied Mathematics
The Kemeny Constant for Finite Homogeneous Ergodic Markov Chains
Journal of Scientific Computing
An Inner-Outer Iteration for Computing PageRank
SIAM Journal on Scientific Computing
Ergodicity Coefficients Defined by Vector Norms
SIAM Journal on Matrix Analysis and Applications
Competitivity groups on social network sites
Mathematical and Computer Modelling: An International Journal
Accelerating the Arnoldi-Type Algorithm for the PageRank Problem and the ProteinRank Problem
Journal of Scientific Computing
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We consider the web hyperlink matrix used by Google for computing the PageRank whose form is given by A(c)=[cP +(1-c)E]T, where P is a row stochastic matrix, E is a row stochastic rank one matrix, and $c\in [0,1]$. We determine the analytic expression of the Jordan form of A(c) and, in particular, a rational formula for the PageRank in terms of c. The use of extrapolation procedures is very promising for the efficient computation of the PageRank when c is close or equal to 1.