PageRank
A demonstration of the PageRank algorithm, using Eigenvectors to assign significance to HTML pages
Install / Use
/learn @SishaarRao/PageRankREADME
PageRank Demonstration
This repository is a demonstration of the applications of Linear Algebra, namely Eigenvector calculations, to the Pagerank algorithms made famous by Google
I wrote about how this algorithm works here!
Requirements
This Pagerank demonstration requires Python 3.x and Bash 4.x
$ python3 --version
$ bash --version
Additionally, this demo employs Scipy and Numpy. Details can be found in requirements.txt
Usage
Simply run the main.py file and you'll be given the information on the Pageranks for the given files located in Pages/
$ python3 main.py
Sources
I heavily consulted this paper published by Rose Hulman to learn how exactly PageRank works. You can download my annotated copy here!
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