PageRank

Predictive Analytics using Networked Data in R

María Óskarsdóttir, Ph.D.

Post-doctoral researcher

The PageRank algorithm

$\textrm{PageRank}_J= \alpha\cdot(\frac{1}{3}\cdot\textrm{PageRank}_H$

$ + \frac{1}{4}\cdot\textrm{PageRank}_I) +(1-\alpha)\cdot e_J $

The PageRank algorithm

$\vec{PR}=\alpha \cdot A \cdot \vec{PR} + (1-\alpha)\cdot \vec{e}$

page.rank(g)

$vector
         A          B          C          D          E          F          G 
0.10238312 0.07917232 0.10164910 0.14693274 0.07953551 0.10335821 0.12732387 
         H          I          J 
0.08675903 0.10994175 0.06294435 

$value
[1] 1

$options
NULL

Personalized PageRank

page.rank(g,
 personalized = c(1,0,0,0,0,0,0,0,0,0))

$vector
         A          B          C          D          E 
0.25528911 0.10363533 0.12156935 0.16625582 0.09366836
         F          G          H          I          J
0.07466596 0.08473039 0.03285162 0.04785657 0.01947748 

$value
[1] 1

$options
NULL

Let's practice!

Predictive Analytics using Networked Data in R