PageRank™ is an algorithm used by the Google search engine to rank websites in its search results. PageRank measures the importance of a page by counting the quantity and quality of links pointing to it.

It's not the only algorithm used by Google to rank web pages, but it's the first one used by the company and the best known. Its properties are widely discussed by experts in search engine optimization ( SEO ).

The PageRank process was patented by Stanford University in the United States under number 6,285,999. Only the name PageRank is a registered trademark of Google . Google holds the exclusive licensing rights to the PageRank patent.

Stanford University received 1.8 million shares of Google stock in exchange for the use of the patent. The shares were sold in 2005 for $336 million.

In constructing the PageRank metric, the web is viewed as a network of citations; each node corresponds to a page, and each link corresponds to a reference from one page to another (hyperlink). The metric assigns a value to each node (page) in the network; a higher value corresponds to a more important node in the network.

From a network theory perspective, PageRank is a centrality metric. This metric leverages the structure of hyperlinks on the web to determine the value for each page on the network. A hyperlink to a page counts as a supporting "vote".

A page's PageRank value depends on the number of pages and the PageRank metric of those pages that point to it. A page has a higher PageRank value if:

• There are many pages pointing to you.
• There are several pages linking to you with a high PageRank metric (a page is important if important pages link to it).

PageRank metric

PageRank metric for nodes in a simple network, expressed as a percentage. (Google uses a logarithmic scale).

Node C has a higher PageRank value than node E, even though there are few connections to C, the connection to C comes from an important node and therefore has a high value.

If a user starts at a random node with an 85% probability of choosing a random link from the node they are currently visiting, and a 15% probability of jumping to a randomly chosen node from the entire network, that user will reach node E 8.1% of the time. (The 15% probability of jumping to an arbitrary node corresponds to a damping factor of 85%).

Without buffering, any user would end up on nodes A, B, or C, and all others would have a PageRank value of zero.

Through the use of the damping factor, node A is connected to all nodes in the network, even if it has no connections to other nodes.

Google and PageRank

The PageRank system is used by the  Google search engine to help determine the relevance or importance of a page . It was developed by Google founders Larry Page and Sergey Brin while they were students at Stanford University in 1998 .

Google maintains a list of billions of pages in order of importance; that is, each page has its importance on the Web as a whole. This Page Database keeps everything from the most important page in the world to the least important. This importance is determined by the number of votes a page receives. A vote is a link anywhere on the Web to that page. Votes for more important pages are worth more than votes for less important pages.

According to several people, this page ranking criterion is quite democratic, reflecting what the "Web thinks" about a given term. Remember that around ten billion pages are taken into account. The quality of the most important pages is naturally guaranteed, ranked, and chosen by the Web itself. Furthermore, all pages have the same chance of rising in this list, gaining votes across the Web.

A good unit of measurement for defining a page's PageRank can be the percentage (%) of pages it is most important to. For example, if a page has a PageRank of 33%, it means it is more important than one-third of the entire web. If its PageRank is 99%, it means it is superior to almost all other pages on the web.

However, it is possible to manipulate PageRank by assigning links that are out of context with the page's purpose, modifying the ordering of results in searches and inducing irrelevant or biased results. A recent example of this is the search for " failure" or "miserable failure," which returned as the first site White House biography US President George W. Bush , followed by the page of Michael Moore , a declared enemy of the US president. This process became known as Googlebombing . Despite this, Google has removed some results resulting from "Googlebombing."

The story of the creation of PageRank.

PageRank was developed at Stanford University by Larry Page (hence the name PageRank) and Sergey Brin in 1996, as part of a research project on a new type of search engine. Sergey Brin had the idea that information on the web could be ordered in a hierarchy of "link popularity": A page is more important if it has more hyperlinks pointing to it. It was co-authored by Rajeev Motwani and Terry Winograd . The first paper on the project, describing the PageRank metric and the initial prototype of the Google search engine, was published in 1998. Soon after, Page and Brin founded Google Inc., the company behind the Google search engine.

The PageRank metric was inspired by analysis , developed by Eugene Garfield in 1950 at the University of Pennsylvania, and by the "Hyper Search" method, developed by Massimo Marchiori at the University of Padua. In the same year that PageRank was introduced (1998), Jon Kleinberg published his work on HITS. The founders of Google cited Marchiori and Kleinberg in their original article.

A search engine called “RankDex” from IDD Information Services, designed by Robin Li since 1996, already explored a strategy for scoring and ranking pages. The technology used in RankDex was patented in 1999 and later used when Li founded Baidu in China. Li's work is referenced in some patents, including Google's search methods, and Larry Page's.

To learn more about PageRank, visit the Wikipedia page .