I am trying to implement the PageRank algorithm described in this paper (Fig. 1). Here is the breakdown of the steps:
http://www.louismullie.com/algo.png
where:
pT
is a probability distribution for the random walk (typically, each element is1/N
where N is the total number of elements)P
is the connectivity matrix wherep(i,j) = {1 or 0} / # outbound links
.
I understand the rationale for the first two steps well. In the following equation,
step 2 solves for the second term. However, I don't understand the rationale behind steps 3-4. In particular, I don't see how adding omega * pT
in the description of the algorithm amounts to adding (1-d)/N
in the equation shown above. As a result, the output I am getting with the two methods differ. Can anybody enlighten me?