The PageRank algorithm (a sequence of instructions, basically) was originally created at Stanford University by Larry Page hence it is called PageRank, or at least that’s what it says in The Google Story, by David Vise and Mark Malseed (2005).

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Mathematical PageRanks (out of 100) for a simple network


(PageRanks reported by Google are rescaled logarithmically). Page C has a higher PageRank than Page E, even though it has fewer links to it: the link it has is much higher valued.


A web surfer who chooses a random link on every page (but with 15% likelihood jumps to a random page on the whole web) is going to be on Page E for 8.1% of the time. (The 15% likelihood of jumping to an arbitrary page corresponds to a damping factor of 85%.) Without damping, all web surfers would eventually end up on Pages A, B, or C, and all other pages would have PageRank zero. Page A is assumed to link to all pages in the web, because it has no outgoing links.


Source: Wikaepedia


Internal link structure


This is why contextual linking is so important, the more links to an internal page from other internal pages the better. For example:


FIG 1: All pages in this example would have the same PR


FIG 2: This example would give A the highest PR but B and C would be weak as they are leaking PR with no internal linking to make it up


FIG 3: This linking example would give A a high PR with B the second highest PR and C would end up being a weak PR page