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URN: urn:nbn:de:0030-drops-10628
URL: http://drops.dagstuhl.de/opus/volltexte/2007/1062/

Gray, Andrew P. ; Greif, Chen ; Lau, Tracy

An Inner/Outer Stationary Iteration for Computing PageRank

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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.

BibTeX - Entry

@InProceedings{gray_et_al:DSP:2007:1062,
  author =	{Andrew P. Gray and Chen Greif and Tracy Lau},
  title =	{An Inner/Outer Stationary Iteration for Computing PageRank},
  booktitle =	{Web Information Retrieval and Linear Algebra Algorithms},
  year =	{2007},
  editor =	{Andreas Frommer and Michael W. Mahoney and Daniel B. Szyld},
  number =	{07071},
  series =	{Dagstuhl Seminar Proceedings},
  ISSN =	{1862-4405},
  publisher =	{Internationales Begegnungs- und Forschungszentrum f{\"u}r Informatik (IBFI), Schloss Dagstuhl, Germany},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2007/1062},
  annote =	{Keywords: PageRank, power method, stationary method, inner/outer iterations, damping factor}
}

Keywords: PageRank, power method, stationary method, inner/outer iterations, damping factor
Seminar: 07071 - Web Information Retrieval and Linear Algebra Algorithms
Issue date: 2007
Date of publication: 28.06.2007


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