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Abstract: The PageRank algorithm, used in the Google search engine, greatly improves the results of Web search by taking into account the link structure of the Web. PageRank assigns to a page a score proportional to the number of times a random surfer would visit that page, if it surfed indefinitely from page to page, following all outlinks from a page with equal probability. We propose to improve PageRank by using a more intelligent surfer, one that is guided by a probabilistic model of the relevance of ... (Update)
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BibTeX entry: (Update)
Matthew Richardson and Pedro Domingos. The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank, volume 14. MIT Press, Cambridge, MA, 2002 (To appear). http://citeseer.ist.psu.edu/article/richardson02intelligent.html More
@inproceedings{ mr+pd:pagerank,
author = "Mathew Richardson and Pedro Domingos",
title = "{T}he {I}ntelligent {S}urfer:
{P}robabilistic {C}ombination of {L}ink and {C}ontent
{I}nformation in {P}age{R}ank",
booktitle = "Advances in Neural Information Processing Systems 14",
publisher = "MIT Press",
year = 2002,
url = "citeseer.ist.psu.edu/article/richardson02intelligent.html",
url = "www.cs.washington.edu/homes/mattr/research.htm",
url = "citeseer.nj.nec.com/460350.html" }
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The anatomy of a large-scale hypertextual Web search engine
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Authoritative sources in a hyperlinked environment
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The PageRank citation ranking: Bringing order to the web
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What is this page known (context) - Rafiei, Mendelzon
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