Distributed PageRank computation based on iterative aggregation-disaggregation methods
Proceedings of the 14th ACM international conference on Information and knowledge management
On computing PageRank via lumping the Google matrix
Journal of Computational and Applied Mathematics
Iterative aggregation: disaggregation methods and ordering algorithms
Proceedings of the 3rd International Conference on Performance Evaluation Methodologies and Tools
PARA'06 Proceedings of the 8th international conference on Applied parallel computing: state of the art in scientific computing
Google PageRanking problem: The model and the analysis
Journal of Computational and Applied Mathematics
Convergence of multi-level iterative aggregation-disaggregation methods
Journal of Computational and Applied Mathematics
Ergodicity Coefficients Defined by Vector Norms
SIAM Journal on Matrix Analysis and Applications
NCDawareRank: a novel ranking method that exploits the decomposable structure of the web
Proceedings of the sixth ACM international conference on Web search and data mining
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The PageRank updating algorithm proposed by Langville and Meyer is a special case of an iterative aggregation/disaggregation (SIAD) method for computing stationary distributions of very large Markov chains. It is designed, in particular, to speed up the determination of PageRank, which is used by the search engine Google in the ranking of web pages. In this paper the convergence, in exact arithmetic, of the SIAD method is analyzed. The SIAD method is expressed as the power method preconditioned by a partial LU factorization. This leads to a simple derivation of the asymptotic convergence rate of the SIAD method. It is known that the power method applied to the Google matrix always converges, and we show that the asymptotic convergence rate of the SIAD method is at least as good as that of the power method. Furthermore, by exploiting the hyperlink structure of the web it can be shown that the asymptotic convergence rate of the SIAD method applied to the Google matrix can be made strictly faster than that of the power method.