Algorithm to find Google PageRank
Google PageRank works by counting the number and quality of links to a page to determine a rough estimate of how important
the website is. The underlying assumption is that more important websites are likely to receive more links from other websites.
PageRank is a link analysis algorithm and it assigns a numerical weighting to each element of a hyperlinked set of documents, such as the WWW, with the purpose of measuring its relative importance within the set. The algorithm may be applied to any collection of entities with reciprocal quotations and references.
Google Pagerank Algorithm.
The original PageRank algorithm was described by Lawrence Page and Sergey Brin in several publications. It is given by
PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn))
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.
Google works because it relies on the millions of individuals posting links on websites to help determine which other sites offer content of value. Google assesses the importance of every web page using a variety of techniques, including its patented PageRank algorithm which analyzes which sites have been voted the best sources of information by other pages across the web.