What is Page Rank Blog You
What is Page Rank Blog You
PageRank is a patented algorithm that serves to determine which web sites are more important / popular. PageRank is one of the main features of the Google search engine and created by its founder, Larry Page and Sergey Brin who is a Ph.D. student Stanford University.Then how to work the Page Rank?
A site will be more popular if more and more other sites that put a link that leads to a site, assuming the content / site content is more useful than the content / content of other sites. PageRank is calculated with a scale of 1-10.Example: A site that has a Pagerank 9 will in the first rank in the search list to Google than sites that have a Pagerank 8 and then onwards are smaller.
Many ways to use search engines to determine the quality / ranking of a web page, ranging from the use of META Tags, the contents of the document, the emphasis on content and many other techniques or combination of techniques that may be used. Link popularity, a technology developed to improve the shortcomings of other technologies (Meta Keywords, Meta Description) can rigged with a special page designed for search engines or so-called doorway pages. With the algorithms 'PageRank' is, in every page will be inbound link (incoming link) and outbound links (links keuar) of each web page.
PageRank, has the same basic concept of link popularity, but not only consider the "number of" inbound and outbound links. The approach used is a page would be considered important if other pages have a link to that page. A page will also become increasingly important if other pages have a rank (pagerank) height refers to the page.
With the approach used PageRank, the process occurs recursively where a ranking will be determined by the ranking of web pages ranking is determined by the ranking of other web pages have a link to that page. This process means a process that is repeated (recursively). In cyberspace, there are millions and even billions of web pages. Therefore a web page ranking is determined from the overall link structure of web pages that exist in cyberspace. A process that is very large and complex.
Want to know the page rank algorithm is not?From the approach already described in the article the concept of PageRank, Lawrence Page and Sergey Brin made pagerank algorithm as below:
Initial algorithm PR (A) = (1-d) + d ((PR (T1) / C (T1)) + ... + (PR (Tn) / C (Tn)))
One other published alogtima PR (A) = (1-d) / N + d ((PR (T1) / C (T1)) + ... + (PR (Tn) / C (Tn)))
* PR (A) is the PageRank page A* PR (T1) is the PageRank of page T1 refer to page A* C (T1) is the number of outgoing links (outbound links) on page T1* D is a damping factor which can be between 0 and 1.* N is the total number of web pages (which is indexed by google)
Random surfer model is an approach that describes how a visitor actually performed in front of a web page. This means the odds or probability that a user clicks on a link is proportional to the number of links on that page. This approach is used so that the pagerank pagerank of incoming links (inbound links) are not directly distributed to the intended page, but divided by the number of outbound links (outbound links) that exist on the page. It was all too consider this fair. Because can you imagine what would happen if a page with a high ranking refers to many pages, may not be relevant pagerank technology used.
This method also has the approach that a user will not click all links on a webpage. Therefore, PageRank damping factor used to reduce the value of the distributed pagerank of a page to another page. The probability that a user continues mengkilk all links on a page is determined by the value of damping factor (d) a value between 0 to 1. High value of damping factor means that a user would click on a page more until he moved to another page. Once the user moves the page, then the probability diimplemntasikan into the pagerank algorithm as a constant (1-d). By removing the variable of inbound links (incoming links), then the possibility of a user to move to another page is (1-d), this will make the pagerank always be at its minimum.
In another pagerank algorithm, there is a value of N which owns the total number of web pages, so a user has a probability of visiting a page divided by the total number of pages that exist. Sebaagai example, if a page has a pagerank of 2 and a total of 100 web pages in a hundred times the visit he visited that page as much as 2 times (note, this is a probability).
Wahhh Long amaaaaaaaaaaattt diatass sempet yet I also read everything I wrote Copas from wikipedia.org om heheheeee yawdah deh but before you dapet pagerank you have to read how to list on searach engine ... when it's let's please check the page rank you are under the
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Wahh tools above I also took from prchecker.info so more you can visit the website okey ...
Rio've already Capekkkk But yes SEO tips will then be followed okey ..Good luck and Success
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