Google PageRank for Search Engine Optimization (SEO)

The term "PageRank" refers to a specialized algorithm that measures the importance of a website page in the Google Search results. The algorithm counts the number of links there are to the webpage from other sites and also analyses the quality of these links. This gives a general idea of how important the page and the website are. The algorithm takes into account a commonsense assumption that websites with greater importance are more likely to have more inbound links from other sites.

Google uses this algorithm along with other algorithms to determine the order of pages displayed in its search results. PageRank was the first algorithm that Google used and even to this day it remains the best known.

PageRank Explained

PageRank uses a special formula to analyze links amongst documents that are hyperlinked across the Internet. The purpose of the algorithm is to measure the importance of different pages within the entire network. Certain authority hubs like, etc. are taken into consideration with the algorithm. Getting a link back from an authority site would provide an impressive vote of support for a website, and should increase the PageRank value of that page.

History of PageRank

PageRank was first developed at Stanford University by Sergey Brin and Larry Page in 1996. Back then it was created as a part of a search engine research project. Brin believed that a hierarchy of pages could be formed based on the link popularity of the separate pages. A page with more links, for example, would receive a higher ranking.

The name "PageRank" was formed using a combination of Larry Page’s last name and a page rank concept and the name is trademarked by Google. It is also patented but the patent belongs to Stanford University, which has provided Google with the exclusive patent rights to it.

PageRank Algorithm

The algorithm is based on a distribution of probability that an individual will click randomly on various links to land on a certain page. A numeric value between 0 - 1 is assigned to the probability. If a page has a PageRank of 0.5, for example, the chance of a person landing on it from clicking on a link is about 50%.

The formula for PageRank uses a random surfer model and assumes that a surfer gets bored after a certain number of clicks and then switches over to another random page. If a page contains no outbound links, it is then known as a sink and the surfing process is terminated. When this surfer lands on a single sink page the algorithm randomly chooses another URL automatically to get the surfing started again.

PageRank is recalculated every time Google crawls the Internet and the algorithm continues to favour pages that are older. Naturally, a page that is new won't have as many links as an older page - even if the content on it is very good. This algorithm continues to be used along with other algorithms by Google to rank sites on the search engine but PageRank can also be used for link recommendations and predictions and for SEO analysis.