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 format]
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.
The EigenTrust Algorithm for Reputation Management in P2P Networks
An eingenvalues algorithm for calculating reputation in P2P networks and isolating malicious peers. There is a relationship with PageRank algorithm. [PDF]
Exploiting the Block Structure of the Web for Computing PageRank
A hierarchical approach for computing PageRank. The local PageRanks of page for each host are computed independently and then used to compute the global PageRank of Web Graph. [PDF]
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.
Improved Algorithms for Topic Distillation in Hyperlinked Environments
Given a typical user query to find quality documents related to the query topic. It uses an Hits variation.
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.
Improvement to Clever Algorithm
A Kleimberg's algorithm improvement. [PDF format]
The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank
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. [PDF format]
Larry Page Describes PageRank
Postscript-format slides which introduces citation importance ranking by Larry Page, Google's founder.
Link Analysis, Eigenvectors, and Stability
Do Hits and PageRank (and some variations) give stable rankings under small perturbations to the linkage patterns? [PS format]
The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity
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. [PDF format]
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 format]
PageRank as a Random Walk
A general framework for measuring the quality of an index and providing the background on the PageRank and Random Walks. Imagine a Web surfer who wanders the Web. At each step, he/she either jumps to a page on the Web chosen uniformly at random, or follows a link chosen from those on the current page.
PageRank Calculation Techniques
Describes efficient techniques for computing PageRank. [PDF]
PageRank Calculation with Lossy Encoding
Lossy encoding for large scale PageRank calculation. [PDF]
PageRank Computation Methods
A poster paper by Stanford db group which describes iterative methods for calculating PageRank. [PDF format]
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