Book Recommendation System: Hybrid Approach

A hybrid book recommendation system is designed to enhance user experience by providing personalized suggestions based on user preferences. This model integrates contentbased and collaborative filtering techniques for improved recommendations. It addresses three scenarios: new users receive recommendations based on book rankings, returning users are served recommendations based on prior interactions, and diverse algorithms handle cases with no prior user interaction. The content-based approach utilizes cosine similarity for a book similarity matrix, while collaborative filtering employs a user-item matrix evaluated using the ALS algorithm. This system demonstrates an effective framework for generating tailored recommendations.