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Page ranking algorithm

Page ranking algorithmOnce the most important part of Google’s ranking system, and now one of hundreds of search engines, the Page ranking algorithm is an important part of search engine optimization (SEO) past and present history. Named after Larry Page, PageRank is a link analysis algorithm applied by that assigns a number or rank to each hyperlinked web page within the World Wide Web.

To illustrate the effects of addional web pages in defining page rank, take a look at a hierachically structured web site consisting of 3 pages A, B and C, joined by an additional page D on the hierarchically lower level. The site has no outbound links. A link from page X which has no outbound links and PageRank of 10 points to page A. At damping factor d of 0.75, equations for the single pages' PageRank values before adding page D are given by:

PR(A) = 0.25 + 0.75 (10 + PR(B) + PR(C))
PR(B) = PR(C) = 0.25 + 0.75 (PR(A) / 2)

A link from page A to page B is interpreted a vote, by page A, for page B. In Google Page ranking algorithm page that casts the vote is also analyzed. "Votes" made by competent web sites weigh more heavily and give opportunity to linked site to be considered as qualitative one. Solving the above equations give us the follwing PageRank values:
PR(A) = 260/14
PR(B) = 101/14
PR(C) = 101/14

Sites with high Google PageRank get a higher ranking in Google results. Further, since Google is currently the world's most popular search engine, the ranking a site receives in its search results has a significant impact on the volume of visitor traffic for that site. Web pages are important themselves if other important web pages link to them. It is not necessary for a page to have many inbound links to rank well. A single link from a high ranking page is sufficient. We'll see this soon, how it happens. After adding page D in our example, the equations for the pages' PageRank values are given by:

PR(A) = 0.25 + 0.75 (10 + PR(B) + PR(C) + PR(D))
PR(B) = PR(C) = PR(D) = 0.25 + 0.75 (PR(A) / 3)

Solving these equations gives us the follwing PageRank values:

PR(A) = 266/14
PR(B) = 70/14
PR(C) = 70/14
PR(D) = 70/14

As to be expected since our example site has no outbound links, after adding page D, the accumulated PageRank of all pages increases by one from 33 to 34. Further, the PageRank of page A rises marginally. In contrast, the PageRank of pages B and C depletes substantially.

Web page that has links from many pages with high Google PageRank receives a high rank itself. But only relevant links, which are connected to your sphere and are useful for your customers, could be valued. The absence of links means that there is no support for that page and it will not get satisfactory Google PageRank.

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