Computers

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]

HITs is a link-structure analysis algorithm which ranks pages by "authorities" (pages which have many incoming links and provide the best source of information on a given topic) and "hubs" (pages which have many outgoing links and provide useful lists of possibly relevant pages). Ranking is performed at query time.

This method uses query dependent importance scores and a probabilistic approach to improve upon PageRank. It pre-computes importance scores offline for every possible text query.

This paper describes a joint probabilistic model for modeling the contents and inter-connectivity of document collections such as sets of web pages or research paper archives.

About the using of PageRank in Web Track 8 "large" and "small" datasets.

About the using of Link Popularity in Web Track 9 datasets.

Information on the algorithm, how to increase PageRank, what diminishes it and how to distribute PageRank within a website.

Lawrence Page's PageRank Patent.

Lossy encoding for large scale PageRank calculation.

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. Ranking is performed at indexing time. Used by Google.