Directory of By Context Resources

Home > Computers > Software > Information Retrieval > Ranking > By Context

Link popularity ranking. Algorithms are eigenvector methods for identifying "authoritative" or "influential" articles, given hyperlink or citation information.

Resources in This Category

• Adaptive On-Line Page Importance Computation

  http://www2003.org/cdrom/papers/refereed/p007/p7-abiteboul.html
  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.

• Authoritative Sources in a Hyperlinked Environment

  http://www.cs.cornell.edu/home/kleinber/auth.pdf
  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.

• DiscoWeb: Discovering Web Communities Via Link Analysis

  http://www.research.rutgers.edu/~davison/discoweb/
  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

  http://www10.org/cdrom/papers/314/
  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.

• Larry Page Describes PageRank

  http://www-db.stanford.edu/~backrub/pageranksub.ps
  Postscript-format slides which introduces citation importance ranking by Larry Page, Google's founder.

• PageRank Calculation with Lossy Encoding

  http://www-db.stanford.edu/~taherh/papers/encoding-pagerank.pdf
  Lossy encoding for large scale PageRank calculation.

• PageRank U.S. Patent 6,285,999

  http://patft.uspto.gov/netacgi/nph-Parser?patentnumber=6285999
  Lawrence Page's PageRank Patent.

• SALSA: The Stochastic Approach for Link-Structure Analysis

  http://www.cs.technion.ac.il/~moran/r/PS/lm-feb01.ps
  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

  http://pr.efactory.de/
  Information on the algorithm, how to increase PageRank, what diminishes it and how to distribute PageRank within a website.

• The Clever Project

  http://www.almaden.ibm.com/cs/k53/clever.html
  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.

• The Intelligent Surfer: Probabilistic Combination of Link and Content Information in PageRank

  http://www.cs.washington.edu/homes/pedrod/papers/nips01b.pdf
  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.

• The Missing Link - A Probabilistic Model of Document Content and Hypertext Connectivity

  http://www.cs.cmu.edu/~cohn/papers/nips00.pdf
  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.

• The PageRank Citation Ranking: Bringing Order to the Web

  http://ilpubs.stanford.edu:8090/422/
  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.

• Web-Trec 8 and PageRank

  http://trec.nist.gov/pubs/trec8/papers/acsys.pdf
  About the using of PageRank in Web Track 8 "large" and "small" datasets.

• Web-Trec 9 and Link Popularity

  http://trec.nist.gov/pubs/trec9/papers/unine9.pdf
  About the using of Link Popularity in Web Track 9 datasets.

• What is this Page Known for? Computing Web Page Reputations,

  http://www.cs.ualberta.ca/~drafiei/papers/www9.ps
  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]

• WWW2003 - Scaling Personalized Web Search

  http://www2003.org/cdrom/papers/refereed/p185/html/p185-jeh.html
  Presentation paper. Link Popularity algorithms biased according to a user-specified set of given interesting pages.

 

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