Link text (anchor text)

   Text of any about inbound links page is vital in the ranking of search results. The anchor (or link) text is the text between the HTML tags «A» and «/ A» and is displayed as text that you click in a browser to go to a new page. If the link text contains relevant keywords, search engine considers it a very important additional recommendation that site actually contains valuable information relevant to the search.

    The importance of referring sites
 
As link text, the search engines also take into account the contents of general information refers to any website.

   Example: Suppose that we are using SEO to promote a car sales resource. In this case, a link from a site about car repair will be much more important than a similar link from a site about gardening. The first link has been published in one source having a similar theme so it will be more important to the search engines.

    Google PageRank - theoretical basics
   Google Company is the first company to patent system regardless of inbound links. The algorithm was named PageRank. In this section, we will describe the algorithm and how it can affect the search result ranking.

   PageRank is estimated separately for each web site and determined by PageRank (citation) of other websites dealing with. This is a kind of "virtuous circle." The main task is to find a criterion that determines the importance of the page. In the case of PageRank, it is possible the frequency of visits to a site.

   I will now describe how the user's behavior when following links to surf the network is modeled. It is assumed that the user starts viewing sites from some random site. Then he or she follows links to other Internet resources. There is always a possibility that the user can leave a country without following any links from outside and start viewing documents from a random page. PageRank algorithm assesses the probability of this event as 0.15 at each step. Probability that our user continues surfing by following one of the links available on the current page is therefore 0.85, assuming that all links are equal in this case. If he or she continues surfing indefinitely, popular pages will be visited many times more than less popular sites.

   PageRank of a web page specified is defined so as the possibility that a user may visit the website. It follows that the sum of the probabilities for all web sites is exactly because the user is supposed to visit at least one site at any given moment.

   Since it is not always convenient to work with these probabilities PageRank can be transformed mathematically into a more easily understood number for viewing. For example, we are used to seeing a PageRank number between zero and ten in Google Toolbar.

   According to the ranking model described above:
   - Each page on the Net (even if there are no inbound links to it) initially has a PageRank greater than zero, although it will be very small. There is a small chance that a user can navigate to it by accident.
   - Each page has external connection distributes part of its PageRank reference site. PageRank contributed to these linked sites, is inversely proportional to the total number of links on the linked-from page - the more links there are, the lower the PageRank allocated to each on-site.
   - PageRank a "damping factor" is applied in this process so that the total on page spread is reduced by 15%. This is equal to the probability, as described above, the user will not visit any of the related pages, but will navigate to an unrelated website.

   Let's see how this PageRank process might affect the process of ranking search results. We say "may" because the pure PageRank algorithm just described is not used in the Google algorithm for quite a while now. We will discuss the most current and sophisticated version soon. There is nothing difficult about the PageRank influence - after the search engine finds a number of relevant documents (using internal criteria text), they can be divided according PageRank that it would be logical to assume that a document has a number largest high-quality inbound links contain valuable information.

   Thus, the PageRank algorithm "pushes up" those documents that are most popular outside the search engine.