PageRank : An Efficient Indicator of Popularity

The term PageRank is an official trademark of Google. The process of PageRank has also been patented under U.S. Patent 6,285,999. The patent is, however, assigned to Stanford University instead of Google. Still, Google owns the exclusive license rights of the patent from the Stanford University. The said university had earned shares of Google amounting to 1.8 million in exchange for the use of this patent. In 2005, the shares were sold for $336 million.

PageRank is used by Google Internet search engine as a link analysis algorithm. Its function is to assign numerical weighting for the elements of a certain hyperlinked set of documents like the World Wide Web. Its main purpose is to measure how relatively important it is within the set. PageRank is the result of a ballot amongst various pages in the internet as to how important a particular page is. A hyperlink to the page is counted as one vote in support of that page.

For instance, a page which had been linked to by various pages with high PageRank gets a high ranking itself. However, no links to a particular web page implies that no support had been given for that page.

Google is that one that gives a numeric weighting for every web page. The numeric weighting ranges from 0 to 10. This PageRank determines the importance of a site based on the analysis of Google. The PageRank of a page is based as to how many inbound links and PageRank of the various pages that provide the links. Other factors that influence the PageRank are the relevance of the search words on a particular page and how many visits there are on that page based on the report of the Google toolbar. Google do not give exact details as to how the other factors can influence the PageRank. This is for the purpose of preventing manipulation, Spamdexing and spoofing that can cause inaccuracies and wrong data.

How can the Algorithm of PageRank be explained? PageRank is known as a probability distribution that is being utilized to represent the chances that an individual who is clicking on links randomly will arrive at a specific page. It can be calculated for the collections of documents that are of any size. There is an assumption by different research papers that the distribution is divided evenly amongst all the documents in the collection at the start of the whole process of computation. The computations of PageRank need a number of passes referred to as “iterations”, through the collections in order to adjust approximate values of PageRank. The purpose is to reflect the theoretical value more closely.

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