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URN: urn:nbn:de:0030-drops-10682
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Extrapolation and minimization procedures for the PageRank vector

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Abstract

An important problem in Web search is to determine the importance of
each page. This problem consists in computing, by the power method,
the left principal eigenvector (the PageRank vector) of a matrix
depending on a parameter $c$ which has to be chosen close to 1.
However, when $c$ is close to 1, the problem is ill-conditioned, and
the power method converges slowly. So, the idea developed in this
paper consists in computing the PageRank vector for several values
of $c$, and then to extrapolate them, by a conveniently chosen
rational function, at a point near 1. The choice of this
extrapolating function is based on the mathematical considerations
about the PageRank vector.


BibTeX - Entry

@InProceedings{brezinski_et_al:DagSemProc.07071.9,
  author =	{Brezinski, Claude and Redivo-Zaglia, Michela},
  title =	{{Extrapolation and minimization procedures for the PageRank vector}},
  booktitle =	{Web Information Retrieval and Linear Algebra Algorithms},
  pages =	{1--6},
  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/opus/volltexte/2007/1068},
  URN =		{urn:nbn:de:0030-drops-10682},
  doi =		{10.4230/DagSemProc.07071.9},
  annote =	{Keywords: Extrapolation, PageRank, Web matrix, eigenvector computation.}
}

Keywords: Extrapolation, PageRank, Web matrix, eigenvector computation.
Seminar: 07071 - Web Information Retrieval and Linear Algebra Algorithms
Issue date: 2007
Date of publication: 28.06.2007


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