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Authoritative Sources in a Hyperlinked Environment
- 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. [PDF]
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. Ranking is performed at indexing time. Used by Google.
Adaptive On-Line Page Importance Computation - A good explanation about the convergence of various algorithms. This paper also describes an adaptive and on-line algorithm for computing the page importance. It can be used for focus crawling as well as for search engine's ranking.
The Clever Project - The CLEVER search engine incorporates several algorithms that make use of hyperlink structure for discovering information on the Web. It is an extension of Hits method.
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.
Finding Authorities and Hubs From Link Structures on the World Wide Web - A survey on PageRank, Hits and SALSA. It also describes two Bayesian statistical algorithms for ranking of hyperlinked documents and the concepts of monotonicity and locality, as well as various concepts of distance and similarity between ranking algorithms.
Improvement of HITS-based Algorithms on Web Documents - It proposes a new weighted HITS-based method that assigns appropriate weights to in-links of root documents and combines content analysis with HITS-based algorithms.
PageRank: A Circuital Analysis - It shows some theoretical results for understanding the distribution of the score in the Web according to PageRank. Seven golden rules for building good pages are presented. [PDF]
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]
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.
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 8 and PageRank - About the using of PageRank in Web Track 8 "large" and "small" datasets. [PDF]
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]
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)
- 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. [PDF]
