The PageRank algorithm was developed in 1996 by Larry Page and Segrey Brin when they were graduate students at Stanford University. Google and other search engines compare words in search phrases to words in web pages and use ranking algorithms to determine the most relevant results.

PageRank assigns a score to a set of web pages that indicates their importance. The underlying idea behind PageRank is to model a user who is clicking on web pages and following links from one page

to another. In this framework, important pages are those which:

- have incoming links from many other pages; and/or

- have incoming links from other pages with a high PageRank score

The PageRank algorithm

PageRank is an iterative algorithm that is repeated until a stopping criteria is met. The last iteration gives us the result of the search, which is a score per web page. A high score indicates a very relevant web page whereas a low score indicates a not so relevant web page for a search. Sorting the web

pages by their scores in descending order gives us the order for the result list of a search query.

For describing the PageRank algorithm we define the following symbols:

-> S is the set of all web pages that we are computing the PageRank scores for

-> N = |S| is the total number of web pages

-> .....

the basic idea is calculate the page rank based on the link coming into the current page and number of the link going out of the current page. the calculation is easy but considering heaps of websites, you need a method to speed up the calculation, which parallel programming comes in this part.

i stop here. the reason is, i tried for nearly half an hour to have my formula typed here, but i couldn't. I tried copy paste, from web, typing what i wanted in the ms word then paste here..no luck...so I gave up.

you can find the detailed documents in the Wikipedia and the original article in the Standford University website.

Pamador out

PageRank assigns a score to a set of web pages that indicates their importance. The underlying idea behind PageRank is to model a user who is clicking on web pages and following links from one page

to another. In this framework, important pages are those which:

- have incoming links from many other pages; and/or

- have incoming links from other pages with a high PageRank score

The PageRank algorithm

PageRank is an iterative algorithm that is repeated until a stopping criteria is met. The last iteration gives us the result of the search, which is a score per web page. A high score indicates a very relevant web page whereas a low score indicates a not so relevant web page for a search. Sorting the web

pages by their scores in descending order gives us the order for the result list of a search query.

For describing the PageRank algorithm we define the following symbols:

-> S is the set of all web pages that we are computing the PageRank scores for

-> N = |S| is the total number of web pages

-> .....

the basic idea is calculate the page rank based on the link coming into the current page and number of the link going out of the current page. the calculation is easy but considering heaps of websites, you need a method to speed up the calculation, which parallel programming comes in this part.

i stop here. the reason is, i tried for nearly half an hour to have my formula typed here, but i couldn't. I tried copy paste, from web, typing what i wanted in the ms word then paste here..no luck...so I gave up.

you can find the detailed documents in the Wikipedia and the original article in the Standford University website.

Pamador out

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