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PageRank

A demonstration of the PageRank algorithm, using Eigenvectors to assign significance to HTML pages

Install / Use

/learn @SishaarRao/PageRank
About this skill

Quality Score

0/100

Supported Platforms

Universal

README

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!

Related Skills

View on GitHub
GitHub Stars19
CategoryDevelopment
Updated1y ago
Forks2

Languages

Shell

Security Score

65/100

Audited on Apr 26, 2024

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