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Agencies are working with Google to boost rankings and increase traffic. Google PageRank - Algorithm. The PageRank Algorithm The original PageRank algorithm was described by Lawrence Page and Sergey Brin in several publications. It is given by PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn)) where So, first of all, we see that PageRank does not rank web sites as a whole, but is determined for each page individually. Further, the PageRank of page A is recursively defined by the PageRanks of those pages which link to page A. The PageRank of pages Ti which link to page A does not influence the PageRank of page A uniformly. The weighted PageRank of pages Ti is then added up. Finally, the sum of the weighted PageRanks of all pages Ti is multiplied with a damping factor d which can be set between 0 and 1. The Random Surfer Model In their publications, Lawrence Page and Sergey Brin give a very simple intuitive justification for the PageRank algorithm.
The random surfer visits a web page with a certain probability which derives from the page's PageRank. The Characteristics of PageRank. Webinator Web Index System: Thunderstone. Add your URL to Google. Sitemaps - My sites. One account. All of Google. Sign in to continue to Google Search Console Find my account Forgot password? Sign in with a different account Create account One Google Account for everything Google.