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Google Page Rank

Learn how Google Calculates the Page Rank of your web-page, how to improve it, PR importance, advantages & its assupmtions.
by

Anusha Dinavahi

on 14 August 2013

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Transcript of Google Page Rank

Introduction
Importance of Page Rank
PR adds weight and authority to website
How to Increase Page Rank???
Assumptions about the Page Rank
Site age
Real VS Tool Bar Page Rank
PR is "link analysis algorithm"
Developed at Stanford University in 1996 by Larry Page and Sergey Brin
Page rank is a general algorithm which ranks a page on basis of its "BACK LINKS"
Frequent Indexes
High PR measures web-page's popularity
Advertisers use PR as basis for their Ad placements
Increase Your Site
Create a Network
Back link duration
Content
Real PR is not Tool Bar PR
High PR is not equal to top search ranking
Back link relevancy
Introduction
Importance
Assumptions
Real VS Tool Bar PR
Ideal PR Values
How to Increase PR
PR Algorithm
Random Surfer
Damping Factor
Working of Algorithm
PR Calculation
Maximum PR of a Website
Example
Conclusion



INDEX
Larry Page
Sergey Brin
Mathematical Algorithm based on webgraph created by WWW assuming Pages as nodes and Hyperlinks as edges
Introduction
Sergey Brins idea
PR indicates importance of a particular page
Calculated for each page
PR of a page depends upon the page rank metrics of all the pages that link to it.

Real PR starts from 0.15 to billions
Tool bar PR starts from 0 to 10
Ideal PR values
0-3 = New sites with minimal back links - (2-12 months)
4-5 = Popular sites with fair amount of back links
5-6 = Very popular sites with more inbound links
7-10 = Hero of that niche
PR Algorithm
PR is a probability distribution that is used to represent the likelihhod that a person randomly clicking on links will arrive at a particular page
Initially the distrubution is divided equally among all the pages which lies b/w 0-1, ideally 0.15
Not single computation, requires several sets of computations
Page with PR - 0.15, 0.15% chance that a person randomly clicking on links will arrive to that page
Random Surfer
PR value reflects the chance that the random surfer will land on that page
Concept of Sink Page
To be fair with the pages that are not sinks, each page is given a PR of 0.15
What if the page is Sink Page?
Damping Factor
Random Surfer, randomly clicking on links, eventually stops clicking. The probability that a person will still continue is the "Damping Factor - (d)"
Generally assumed as 0.85
What is Random Surfer?
The DF is subtracted from 1 and is added to the product of dampng factor and the sum of incoming PR scores
Working of Algorithm
Assume 4 webpages in the universe, A, B, C, D
Case 1 - All other pages link to page A
PR(A) = PR(B)+PR(C)+PR(D)
B
A
D
C
Case 2 -
Working of Algorithm
A
B
D
C
PR(A) = PR(B)/2+PR(C)/3+PR(D)/2
Working of Algorithm
Ideally PR of page A is
PR(A) = PR(B)/L(B)+PR(C)/L(C)+PR(D)/L(D)
When the concept of damping factor is been added, PR of page A becomes -
PR(A) = (1-d) + d {PR(B)/L(B)+PR(C)/L(C)+PR(D)/L(D)}
where damping factor d = 0.85
PR calculation
Maximum PR of a website
Total no.of pages in the website*1
If calculated PR is 10 <= Max PR of a website, then the website has bad "linking structure"
Payment care - http://paymentcare.co.uk/
Total no.of valid pages = 150
Max PR of website = 150*1 = 150
calculated PR = Sum of Tool bar PR of all the valid pages = 70
PR loss = 150-70 = 80
Result = Poor linking structure
Example
Conclusion
LINKING STRUCTURE
Full transcript