• Vishakha Kothawal
• Melvin Torde
• Hitesh Thakare
• Kartik Jawale
• Sneha Rathi

Abstract-In the digital age, readers confront an overabundanceof book titles, which poses the problem of how to push theright book candidate based on a reader’s interest. In this work, we propose a Book Recommendation System that provides readers with personalized and meaningful suggestions related to their reading history, ratings, and genres of interest. The recommendations generated by our system are accomplished by using Artificial Intelligence (AI) techniques consisting in: collaborative filtering, deep learning non-collaborative filtering together with advanced graph-ranking algorithms. Our hybrid model attempts at exploiting both explicit inputs from users (e.g., ratings), as well as implicit behavior signals (e.g., browsing events). Indeed, beyond simply making a suggestion to users’ explicit query/rating/input, we add a recommendation component in order to make users more satisfied and improve their interaction experience with our systems via interactive push where potential item discoveries can be triggered implicitly. The system leverages the state-of-the-art AI technologies such as machine learning models to improve recommendations by considering both user sentiment and content quality. Our ultimate goal is to provide a personalized, adaptive and effective reading service for each individual user with a large volume of abundant candidate items.

Keywords:- Book Recommendation System, Artificial Intelligence, Collaborative Filtering, Deep Learning, Graph Ranking Algorithms, Choice Overload, User Preferences, Machine Learning.

"Book fusion: Intelligent Book Recommendations", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.11, Issue 12, page no.c294-c301, December-2024, Available :http://www.jetir.org/papers/JETIR2412231.pdf

"Book fusion: Intelligent Book Recommendations", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.11, Issue 12, page no. ppc294-c301, December-2024, Available at : http://www.jetir.org/papers/JETIR2412231.pdf