Page Rank
Done by: Asem Battah
Supervised by: Dr. Samir Tartir
Introduction:
PageRank is what search engine uses to
determine the importance of a web page. It's
one of many factors used to determine which
pages appear in search results.
The History of PageRank:
PageRank was developed by Google founders
Larry Page and Sergey Brin at Stanford.
At the time that Page and Brin met, search
engines typically linked to pages that had the
highest keyword density, which meant people
could game the system by repeating the same
phrase over and over to attract higher search
page results.
How dose it work?
• PageRank assigns a rank or score to every search result. The
higher the page's score, the further up the search results
list it will appear.
• Scores are partially determined by the number of
other Web pages that link to the target page. Each link is
counted as a vote for the target. The logic behind this is
that pages with high quality content will be linked to more
often than mediocre pages.
• Not all votes are equal. Votes from a high-ranking Web
page count more than votes from low-ranking sites. You
can't really boost one Web page's rank by making a bunch
of empty Web sites linking back to the target page.
Cont.
• The more links a Web page sends out, the more diluted
its voting power becomes. In other words, if a highranking page links to hundreds of other pages, each
individual vote won't count as much as it would if the
page only linked to a few sites.
• Other factors that might affect scoring include the how
long the site has been around, the strength of the
domain name, how and where the keywords appear on
the site and the age of the links going to and from the
site. Google tends to place more value on sites that
have been around for a while.
Pagerank algorithm:
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
Where:
• PR(A) is the PageRank of page A,
• PR(Ti) is the PageRank of pages Ti which link to
page A,
• C(Ti) is the number of outbound links on page Ti
and
• d is a damping factor which can be set between 0
and 1.
Example:
Let us denote by A the transition matrix of the graph, A =
Resources:
• http://www.math.cornell.edu/~mec/Winter20
09/RalucaRemus/Lecture3/lecture3.html
• http://www.howstuffworks.com/googlealgorithm1.htm
• http://pr.efactory.de/e-pagerankalgorithm.shtml
• http://google.about.com/od/searchengineopti
mization/a/pagerankexplain.htm