PageRankTM (PR)

PageRankTM (PR)

is a numeric value that represents how important a website is online. Google becomes the idea that when a web site places a link (link) to another, is in fact a vote for the latter.

The more votes has a page will be considered more important by Google. Moreover, the importance of the page that casts the vote also determines the weight of this vote. In this way, Google calculates the importance of a page thanks to the votes received, taking into account the importance of each page that casts the vote.

PageRankTM (developed by the founders Larry Page and Sergey Brin)is the way Google decides the importance of a page. It is a valuable data because it is one of the factors that determine the position will have a page within the search results. It is not the only factor that Google uses to rank pages, but it is one of the most important.

Keep in mind that not all the links are taken into account by Google. For example, Google filters out and discards the links of pages devoted exclusively to put links (called 'link farms').

In addition, Google admits that a page can not control the links that point to it, but you can check the links page to other pages in place. Therefore, links to a page can not harm it, but it links a page to place penalized sites may be harmful to your PageRankTM.

If a site has PR0, it is usually a site penalized, and may not be intelligent to put a link to her.

One way to know a page is PageRankTM download it the Google search bar (only available for MS IExplorer). Bar appears in the one shown in green PageRankTM value on a scale of 0 to 10. PR10 websites are Yahoo, Microsoft, Adobe, Macromedia, and Google. You have a full list of PR10 sites.

Algorithm

The algorithm 'PageRankTM' was patented in the United States on 8 January 1998 by Larry Page. The original title is "Method for node ranking in a linked database ', and was assigned patent number 6,285,999.

PageRank is a probability distribution used to represent the likelihood that a person randomly clicking on links will arrive at any particular page. PageRank can be calculated for collections of documents of any size. It is assumed in several research papers that the distribution is evenly divided among all documents in the collection at the beginning of the computational process. The PageRank computations require several passes, called "iterations", through the collection to adjust approximate PageRank values to more closely reflect the theoretical true value.

A probability is expressed as a numeric value between 0 and 1. A 0.5 probability is commonly expressed as a "50% chance" of something happening. Hence, a PageRank of 0.5 means there is a 50% chance that a person clicking on a random link will be directed to the document with the 0.5 PageRank.

SERP Rank

The Search engine results page (SERP) is the actual result returned by a search engine in response to a keyword query. The SERP consists of a list of links to web pages with associated text snippets. The SERP rank of a web page refers to the placement of the corresponding link on the SERP, where higher placement means higher SERP rank. The SERP rank of a web page is not only a function of its PageRank, but depends on a relatively large and continuously adjusted set of factors (over 200), commonly referred to by internet marketers as "Google Love".Search engine optimization (SEO) is aimed at achieving the highest possible SERP rank for a website or a set of web pag