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mathematically transformed into a more easily understood number for viewing. For
instance, we are used to seeing a PageRank number between zero and ten on the Google
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 tiny chance that a
user may accidentally navigate to it.
- Each page that has outbound links distributes part of its PageRank to the referenced
page. The PageRank contributed to these linked-to pages is inversely proportional to the
total number of links on the linked-from page – the more links it has, the lower the
PageRank allocated to each linked-to page.
- PageRank A “damping factor” is applied to this process so that the total distributed
page rank is reduced by 15%. This is equivalent to the probability, described above, that
the user will not visit any of the linked-to pages but will navigate to an unrelated website.
Let us now see how this PageRank process might influence the process of ranking
search results. We say “might” because the pure PageRank algorithm just described has
not been used in the Google algorithm for quite a while now. We will discuss a more
current and sophisticated version shortly. There is nothing difficult about the PageRank
influence – after the search engine finds a number of relevant documents (using internal
text criteria), they can be sorted according to the PageRank since it would be logical to
suppose that a document having a larger number of high-quality inbound links contains
the most valuable information.
Thus, the PageRank algorithm "pushes up" those documents that are most popular
outside the search engine as well.
3.6 Google PageRank – practical use
Currently, PageRank is not used directly in the Google algorithm. This is to be
expected since pure PageRank characterizes only the number and the quality of inbound
links to a site, but it completely ignores the text of links and the information content of
referring pages. These factors are important in page ranking and they are taken into
account in later versions of the algorithm. It is thought that the current Google ranking
algorithm ranks pages according to thematic PageRank. In other words, it emphasizes the
importance of links from pages with content related by similar topics or themes. The
exact details of this algorithm are known only to Google developers.
You can determine the PageRank value for any web page with the help of the Google
ToolBar that shows a PageRank value within the range from 0 to 10. It should be noted
that the Google ToolBar does not show the exact PageRank probability value, but the
PageRank range a particular site is in. Each range (from 0 to 10) is defined according to a
Here is an example: each page has a real PageRank value known only to Google. To