Book Recommendation System

Figure : The home page displaying the top 50 books based on popularity.

Figure : The recommend page displaying the user searched book recommendations.

Overview

The Book Recommendation System is a Flask-based web application that offers two main features:

Popularity-Based Recommendation

The home page displays the top 50 books based on popularity, selected based on their average rating and at least 150 reviews. This ensures that the recommended books are widely loved and have a substantial number of ratings.

Personalized Recommendation

In the "Recommend" tab, users can input a book title they are interested in. The system utilizes two recommendation algorithms - Cosine Similarity and Collaborative Filtering - to suggest four similar books. Cosine Similarity compares book similarities based on their features, while Collaborative Filtering recommends books based on similar user preferences.

How to Use

1. Clone the repository to your local machine.
2. Install the required dependencies.
3. Run the Flask app using python app.py.
4. Access the web app in your browser by navigating to http://localhost:5000.

Features

• Top 50 Books: Display a curated list of the top 50 books based on popularity and user ratings.
• Personalized Recommendations: Receive personalized book recommendations by entering a book title of interest.
• Cosine Similarity and Collaborative Filtering: Utilize advanced recommendation algorithms for accurate and relevant book suggestions.

Technologies Used

• Python
• Flask
• Pandas 2.2.1
• Scikit-learn
• HTML/CSS
• Jinja(for HTML templating)

Acknowledgements

Special thanks to Kaggle for providing the latest book dataset used in this project.