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Actually PageRank is an algorithm used to rank the content of web pages. This algorithm is the main part of today's Google engine and used to rank the importance of web pages.

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Actually PageRank is an algorithm used to rank the content of web pages. This algorithm is the main part of today's Google engine and used to rank the importance of web pages.

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PageRank (PR) is an algorithm used by Google Search to rank websites in their search engine results. PageRank was named after Larry Page, one of the founders of Google.

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The search engine that decides page rank is Google. Google's PageRank algorithm is the foundation of its search engine and determines the ranking of web pages in its search results. PageRank is a complex algorithm that evaluates the importance and relevance of web pages based on various factors.

PageRank was developed by Larry Page and Sergey Brin, the founders of Google, while they were Ph.D. students at Stanford University. It was named after Larry Page and is a play on words with "page" referring to web pages.

The PageRank algorithm works by analyzing the link structure of the web. It assigns a numerical value, known as PageRank score, to each web page based on the number and quality of links pointing to it. The more high-quality links a page has, the higher its PageRank score will be.

When a user performs a search query, Google's search engine uses the PageRank algorithm to determine the relevance and importance of web pages that match the query. Pages with higher PageRank scores are considered more relevant and are given higher positions in the search results.

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PageRank algorithmGoogle Algorithm is a link analysis algorithm, named after Larry Page and used by the Google search engine, that assign a numerical weighting to each element of a hyperlinked set of documents.

In short PageRank is a vote by all the other pages on the web and about how important page is. A link to a page is counts as a vote of support.

Equation of PageRank is......

PR(A)=(1-d)+d(PR(T1)/C(T1)+…..+PR(Tn)/C(Tn))

  • PR(Tn)= each page has a notion of its own self value. PR(T1) for the first page in the web all the way up to PR(Tn) for the last page.
  • C(Tn) = each page spreads its vote out evenly among all of its outgoing links. The count or number of outgoing link for page 1 is C(T1), C(Tn) for page n and so on for all pages.
  • PR(Tn)/C(Tn)=I four page (page A) has a back link from page "n" the share of the vote page A will get is PR(Tn)/C(Tn).
  • d= all these fractions of votes is damped down by multiplying it by 0.85(the factor "d").
  • (1-d)= the (1-d) bit at the beginning is a bit of probability math magic so the sum of all web pages or PageRank will be one.

The PageRank of a page depend upon the PageRank of a page pointing to it.

Once the PageRank calculations have settles down, the normalized probability distribution (the average PageRank for all pages) will be 1.0.

PageRank of different sites:

  • The PageRank of Google is 0.9/1
    • The PageRank of facebook is 0.9/1
    • The PageRank of reddit is 0.8/1
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