📚 RecSys — Book Recommendation System

A Flask-based web application that recommends books to users using collaborative filtering and content-based filtering techniques powered by scikit-surprise and scikit-learn.

Features

• Demographic-based initial suggestions – recommends books based on user age and location similarity
• Collaborative filtering – uses KNN with means (via Surprise) to generate personalized recommendations from rating history
• Content-based filtering – uses TF-IDF and cosine similarity on book metadata
• Interactive web UI – built with Flask and Jinja2 templates

Project Structure

flaskr/
├── __init__.py         # Flask app factory
├── main.py             # Routes and recommendation logic
├── static/
│   ├── book_data.csv   # Book metadata
│   ├── book_info.csv   # Additional book info
│   └── Users.csv       # User demographic data
├── templates/
│   └── index.html      # Main UI template
└── tools/
    └── data_tool.py    # Data loading & helper utilities

Setup

1. Create and activate a virtual environment

python3 -m venv venv
source venv/bin/activate

2. Install dependencies

pip install -r requirements.txt

Run the project

flask --app flaskr run --debug

Then open your browser at http://127.0.0.1:5000.

Requirements

• Python 3.10+
• See requirements.txt for full list of dependencies