Building the formula

Let's consider PageRank in the context of the internet. The PageRank algorithm relies on the idea that not all incoming links have the same weight. As an example, consider a backlink from a New York Times article to an article in your blog. It is more important than a link from a website that gets 10 visits a month since it will redirect more users to your blog. So, we would like the New York Times to have more weight than the low-traffic website. The challenge here is to assess the weight of an incoming connection. In the PageRank algorithm, this weight is the importance of the page or the rank of the page. So, we end up with a recursive formula where each page's importance is measured compared to the other pages:

PR(A) = PR(N₁) + ... + PR(N_n)

Here, N_i (i=1...n) is the pages pointing to page A (the incoming relationships).

The PageRank of node A tends to be higher if the sum of the PageRank of the nodes pointing to A is high.

This is not the final...