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The World’s Largest Matrix Computation
"Google's PageRank is an eigenvector of a matrix of order 2.7 billion"
http://www.mathworks.com/company/newsletters/news_notes/clevescorner/oct02_cleve.html
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Extrapolation Methods for Accelerating PageRank Computations
A paper about the computation of PageRank using the standard Power Method and the new Quadratic Extrapolation which computes the principal eigenvector of the Markov matrix representing the Web link graph with an increased speed up of about 50-300%.
http://www.stanford.edu/~sdkamvar/papers/extrapolation.pdf
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Topic -Sensitive Page Rank
Integrates ODP data in PageRank calculation for performing query time probabilistic ranking.
http://www2002.org/CDROM/refereed/127/
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PageRank Calculation with Lossy Encoding
Lossy encoding for large scale PageRank calculation.
http://www-db.stanford.edu/~taherh/papers/encoding-pagerank.pdf
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WWW2003 - Scaling Personalized Web Search
Presentation paper. Link Popularity algorithms biased according to a user-specified set of given interesting pages.
http://www2003.org/cdrom/papers/refereed/p185/html/p185-jeh.html
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DiscoWeb: Discovering Web Communities Via Link Analysis
This paper describes a prototype system, later known as the Teoma Search Engine. It performs a Link Analysis, loosely based on the Kleimberg method, and computed at query time.
http://www.research.rutgers.edu/~davison/discoweb/
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The PageRank Citation Ranking: Bringing Order to the Web
First Stanford paper about PageRank. It is a static ranking, performed at indexing time, which interprets a link from page A to page B as a vote, by page A, for page B. Web is seen as a direct graph and votes recursively propagate from nodes to nodes. Ra
http://ilpubs.stanford.edu:8090/422/
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