In their original paper presenting Google, Larry and Sergey define PageRank like this: PR(A) = (1-d) + d (PR(T1)/C(T1) + ... + PR(Tn)/C(Tn)). We dive into what that really means. Earlier today, Dixon ...

A computational chemist at Washington State University has adapted Google's seminal search algorithm, PageRank, so that instead of mapping trillions of web pages it maps out the shapes and chemical ...

Here's an in-depth look into harmonic centrality, why it's useful for search engines, and how it compares against PageRank. Graphs help us understand the real world better by mathematical abstractions ...