PageRank U.S. Patent 6,285,999
Lawrence Page's PageRank Patent.
PageRank Used to Characterize Web Structure
PageRank's values on the Web follow a power law. An high in-degree of a node does not imply high PageRank, and vice versa. [PDF format]
Probabilistic Combination of Content and Links
It introduces a probabilistic model that integrates link topology (used to identify important pages), anchor text (used to augment the text of cited pages), and activation (spread to linked pages). Experiments are on MSN Directory. [PDF format]
SALSA: The Stochastic Approach for Link-Structure Analysis
A focused search algorithm (SALSA) based on Markov chains. It starts with a query on a broad topic, discards useless links, and then weights the remaining terms. A stochastic crawl is used to discover the authorities on this topic. [PS format]
The Second Eigenvalue of the Google Matrix
A mathematical paper about the convergence of methods used for solving the PageRank Matrix. [PDF]
Survey on Google's PageRank
Information on the algorithm, how to increase PageRank, what diminishes it and how to distribute PageRank within a website.
Topic -Sensitive Page Rank
Integrates ODP data in PageRank calculation for performing query time probabilistic ranking.
Towards Exploiting Link Evolution
It describes how to compute incrementally PageRank when Web graph's link topology changes. [PS format]
Web Page Scoring Systems for Horizontal and Vertical Search
"Random Surfer" model extension. At each step of traversal of the Web graph, the surfer can jump to a random node or follow a hyperlink or follow a back-link (a hyperlink in the inverse direction) or stay in the same node.
Web-Trec 9 and Link Popularity
About the using of Link Popularity in Web Track 9 datasets. [PDF format]
Web-Trec 8 and PageRank
About the using of PageRank in Web Track 8 "large" and "small" datasets. [PDF format]
What is this Page Known for? Computing Web Page Reputations,
PageRank and Hub and Authority generalization based on the topic of Web Pages. Definition of a model where a surfer can move forward (following an out-going link) and backward (following an in-going link in the inverse direction). [PS format]
The World’s Largest Matrix Computation
"Google's PageRank is an eigenvector of a matrix of order 2.7 billion"
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%. [PDF] (May, 2003)
WWW2003 - Scaling Personalized Web Search
Presentation paper. Link Popularity algorithms biased according to a user-specified set of given interesting pages. [PDF] (May, 2003)
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