(Enter summary)
Abstract: The web link graph has a nested block structure:
the vast majority of hyperlinks link pages
on a host to other pages on the same host, and
many of those that do not link pages within the
same domain. We show how to exploit this structure
to speed up the computation of PageRank by
a 3-stage algorithm whereby (1) the local PageRanks
of pages for each host are computed independently
using the link structure of that host,
(2) these local PageRanks are then weighted by
the "importance" of... (Update)
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BibTeX entry: (Update)
S. D. Kamvar, T. H. Haveliwala, C. D. Manning, and G. H. Golub. Exploiting the block structure of the web for computing PageRank. Stanford University Technical Report, 2003. http://citeseer.ist.psu.edu/kamvar03exploiting.html More
@misc{ kamvar03exploiting,
author = "S. Kamvar and T. Haveliwala and C. Manning and G. Golub",
title = "Exploiting the block structure of the web for computing PageRank",
text = "S. D. Kamvar, T. H. Haveliwala, C. D. Manning, and G. H. Golub. Exploiting
the block structure of the web for computing PageRank. Stanford University
Technical Report, 2003.",
year = "2003",
url = "citeseer.ist.psu.edu/kamvar03exploiting.html" }
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The PageRank citation ranking: Bringing order to the web
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Graph structure in the web (context) - Broder, Kumar et al. - 2000
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Topic-sensitive PageRank
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Extrapolation methods for accelerating PageRank computations
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