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In the original form of PageRank, the sum of PageRank over all pages was the total number of pages on the web at that time, so each page in this example would have an initial value of 1. However, later versions of PageRank, and the remainder of this section, assume a probability distribution between 0 and 1.
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.
The webgraph is an example of a scale-free network. Applications. The webgraph is used for: computing the PageRank [5] of the world wide web's pages;
Google PageRank (PR) is a measure from 0 - 10. Google PageRank is based on backlinks. PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites. [1]
Google's rise was largely due to a patented algorithm called PageRank which helps rank web pages that match a given search string. [34] When Google was a Stanford research project, it was nicknamed BackRub because the technology checks backlinks to determine a site's importance.
Numeric examples of PageRank values in a small graph with a damping factor of 0.85. The exact solution is: = ... Page Rank; Usage on bn.wikipedia.org
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