This is a limited edition print with only 250 copies in production.
Lawrence Page, January 9, 1998.
PageRank 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 who is the named inventor on this patent.
Google was founded in 1996 by Larry Page and Sergey Brin while they were Ph.D. students at Stanford University, California. PageRank was the underlying algorithm that set it apart from other online search entities at the time who were still using standard vector spaced models.
PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important the website is. The underlying assumption is that more important websites are likely to receive more links from other websites. It's not the only algorithm used by Google to order search engine results, but it is the first algorithm that was used by the company, and it is the best-known.
This patent titled 'Method for Node Ranking in a Linked Database' was filed on the 9th of January, 1998. Described as a system that can provide "an objective ranking based on the relationship between documents whose content has a large variation in quality and importance. Another aspect of the present invention is to provide a document ranking method that is scalable and can be applied to extremely large databases such as the World Wide Web."
Page and Brin originally nicknamed their new search engine "BackRub", because the system checked backlinks to estimate the importance of a site. Eventually, they changed the name to Google, originating from a misspelling of the word "googol", the number one followed by one hundred zeros.
Alphabet, Inc. (parent company of Google, Inc) now has a market cap of $560B with 70,000 employees worldwide. It is truly amazing to think that this tech behemoth all began with a simple concept, captured in just three diagrams on this patent print.
Want to know more about what a patent is, we have created a description page here.
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