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PageRank is a way of measuring the importance of website pages. According to Google: 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]
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 [1] However, Google claims there will be no more PageRank updates, rendering this metric as outdated. [2]
PageRank estimates the likelihood that a given page will be reached by a web user who randomly surfs the web and follows links from one page to another. In effect, this means that some links are stronger than others, as a higher PageRank page is more likely to be reached by the random web surfer. Page and Brin founded Google in 1998. [16]
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.
A web resource may be (for example) a website, web page, or web directory. [1] A backlink is a reference comparable to a citation. [2] The quantity, quality, and relevance of backlinks for a web page are among the factors that search engines like Google evaluate in order to estimate how important the page is.
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. Other keyword-based methods to rank search results, used by many ...
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