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HOME Software Software Information Retrieval Information Retrieval Ranking Ranking By Context By Context


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  07-January-2012 
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...



 
   
  07-January-2012 
Integrates ODP data in PageRank calculation for performing query time probabilistic ranking.



 
   
  07-January-2012 
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.



 
   
  07-January-2012 
Information on the algorithm, how to increase PageRank, what diminishes it and how to distribute PageRank within a website.



 
   
  07-January-2012 
About the using of PageRank in Web Track 8 "large" and "small" datasets.



 
   
  07-January-2012 
A poster paper by Stanford db group which describes iterative methods for calculating PageRank.



 
   
  07-January-2012 
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.



 
   
  07-January-2012 
Paper by Minhua Wang describing an improvement to Kleimberg's algorithm.



 
   
  07-January-2012 
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.



 
   
  07-January-2012 
"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.


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