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An Inner/Outer Stationary Iteration for Computing PageRank

Authors: Andrew P. Gray, Chen Greif, and Tracy Lau

Published in: Dagstuhl Seminar Proceedings, Volume 7071, Web Information Retrieval and Linear Algebra Algorithms (2007)

Abstract

We present a stationary iterative scheme for PageRank computation. The algorithm is based on a linear system formulation of the problem, uses inner/outer iterations, and amounts to a simple preconditioning technique. It is simple, can be easily implemented and parallelized, and requires minimal storage overhead. Convergence analysis shows that the algorithm is effective for a crude inner tolerance and is not particularly sensitive to the choice of the parameters involved. Numerical examples featuring matrices of dimensions up to approximately $10^7$ confirm the analytical results and demonstrate the accelerated convergence of the algorithm compared to the power method.

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Andrew P. Gray, Chen Greif, and Tracy Lau. An Inner/Outer Stationary Iteration for Computing PageRank. In Web Information Retrieval and Linear Algebra Algorithms. Dagstuhl Seminar Proceedings, Volume 7071, pp. 1-8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2007)

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@InProceedings{gray_et_al:DagSemProc.07071.5,
  author =	{Gray, Andrew P. and Greif, Chen and Lau, Tracy},
  title =	{{An Inner/Outer Stationary Iteration for Computing PageRank}},
  booktitle =	{Web Information Retrieval and Linear Algebra Algorithms},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2007},
  volume =	{7071},
  editor =	{Andreas Frommer and Michael W. Mahoney and Daniel B. Szyld},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/DagSemProc.07071.5},
  URN =		{urn:nbn:de:0030-drops-10628},
  doi =		{10.4230/DagSemProc.07071.5},
  annote =	{Keywords: PageRank, power method, stationary method, inner/outer iterations, damping factor}
}

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An Inner/Outer Stationary Iteration for Computing PageRank

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