News Recommendation algorithm

Summary:

This project builds a personalized News Recommendation System in Go with SQL for tracking user interactions and authorization. It uses Colly for web scraping and caching for faster performance.

Features

• Personalized FYP based on:
  • User's news visit history (categories and recency)
  • Randomized content diversity
• SQL for:
  • User authentication
  • Storing user visit history
• Web scraping powered by the Colly library
• React for the frontend with Tailwind CSS for styling
• Caching and hash sets for optimized performance

Getting started:

Prerequisites:

• MySQL Database
• Golang
• Node.js

Video demonstration:

Watch this video to see the website in action. Video link here

Installation:

• You can install the zip file of the project from here
• If you have git installed type

git clone https://github.com/shaeelhashmi/news-recommendation-algorithm

Execution:

Once in the news-recommendation-algorithm set up your .env file and then run:

go run main.go

Then start the frontend server by typing the following commands:

cd my-project

Once in the directory install the necessary packages.

npm install

After installation start the server.

npm run dev

Setting up .env

The env file has this format:
DBUSER="Your database username"
DBPASS="Database password"
SESSION_KEY="A random key for creating a secure session"