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Google's founders, in their original paper, [31] reported that the PageRank algorithm for a network consisting of 322 million links (in-edges and out-edges) converges to within a tolerable limit in 52 iterations. The convergence in a network of half the above size took approximately 45 iterations.
Fig.1. Google matrix of Wikipedia articles network, written in the bases of PageRank index; fragment of top 200 X 200 matrix elements is shown, total size N=3282257 (from [1]) A Google matrix is a particular stochastic matrix that is used by Google's PageRank algorithm. The matrix represents a graph with edges representing links between pages.
Ranking of query is one of the fundamental problems in information retrieval (IR), [1] the scientific/engineering discipline behind search engines. [2] Given a query q and a collection D of documents that match the query, the problem is to rank, that is, sort, the documents in D according to some criterion so that the "best" results appear early in the result list displayed to the user.
Google PageRank (Google PR) is one of the methods Google uses to determine a page's relevance or importance. Important pages receive a higher PageRank and are more likely to appear at the top of the search results. Google PageRank (PR) is a measure from 0 - 10. Google PageRank is based on backlinks.
TrustRank is an algorithm that conducts link analysis to separate useful webpages from spam and helps search engine rank pages in SERPs (Search Engine Results Pages). It is semi-automated process which means that it needs some human assistance in order to function properly.
Google PageRank of the main English Wikipedia homepage: . 22 October 2002, 41/100(www.wikipedia.org) 3 November 2002, 7/10 1 December 2002, 8/10 10 January 2003, 8/10 15 March 2003, 7/10 (perhaps Google's algorithm was changed?) 12 April 2003, 7/10 30 May 2003, 7/10 2 October 2003, 8/10 7 November 2003, 8/10 30 January 2004, 8/10 22 October 2004, 8/10 24 December 2004, 8/10 2 July 2005, 9/10 ...
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