Page rank is one of the methods Google uses to determine a page’s relevance or importance. It works by counting links and text of the links pointing at a page and/or domain. PageRank is a vote, by all the other pages on the Web, about how important a page is. A link to a page counts as a vote of support. If there’s no link there’s no support.

Google use software called “PageRank” for ranking pages. Google founders Larry Page and Sergey Brin developed it. Though it is very advanced now, the basic logic remained as it is.

Quoting from the original Google paper, PageRank is defined like this:

We assume page A has pages T1...Tn, which point to it (i.e., are citations).
The parameter d is a damping factor, which can be set between 0 and 1.
We usually set d to 0.85.

Also C(A) is defined as the number of links going out of page A.
The PageRank of a page A is given as follows:
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))

Note that the PageRanks form a probability distribution over web pages, so the sum of all web pages' PageRanks will be one.

PageRank or PR (A) can be calculated using a simple iterative algorithm, and corresponds to the principal eigenvector of the normalized link matrix of the web.

PageRank relies on the uniquely democratic nature of the web by using its vast link structure as an indicator of an individual page's value. In essence, Google interprets a link from page A to page B as a vote, by page A, for page B. But, Google looks at more than the sheer volume of votes, or links a page receives; it also analyzes the page that casts the vote. Votes cast by pages that are themselves "important" weigh more heavily and help to make other pages "important."

Important, high-quality sites receive a higher PageRank, which Google remembers each time it conducts a search. Of course, important pages mean nothing to you if they don't match your query. So, Google combines PageRank with sophisticated text-matching techniques to find pages that are both important and relevant to your search. Google goes far beyond the number of times a term appears on a page and examines all aspects of the page's content (and the content of the pages linking to it) to determine if it's a good match for your query.

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