suggest-A-book

A book recommendation system using item-item collaborative filtering. It is a simple implemenation of collaborative filtering approach for recommendation systems. The system recommends books to the user based on their recent read by using k-Nearest neighbors approach on user-item sparse matrix.

Dataset

The dataset used is goodreads-10k dataset that contains 6 million ratings for ten thousand most popular books (https://github.com/zygmuntz/goodbooks-10k).

Prerequisites

Backend (Recommendation system)

• python >= 3.6

Frontend

• node.js >= 10.12.0

Installation steps

Optional: Create virtual environment for python

pip install --user virtualenv
virtualenv env
source env/bin/activate

Clone the repository and install required packages

git clone https://github.com/prati1/suggest-a-book.git
cd suggest-a-book/frontend
npm install
cd ../recommender-api
pip install -r requirements.txt

Generate user-item sparse matrix

Go to recommender-api folder

python sparse_matrix_generator.py

Run recommender api

python recommender_api.py

Run recommender frontend

Go to frontend folder

npm start