TY - JOUR AU - Kavita Kelkar, Jayanti Rathnavel PY - 2017/04/26 Y2 - 2024/03/29 TI - Personalized Book Recommendation System JF - International Journal of Engineering and Computer Science JA - int. jour. eng. com. sci VL - 6 IS - 4 SE - Articles DO - UR - http://ijecs.in/index.php/ijecs/article/view/3787 SP - AB - <p>: Recommender systems are found in many ecommerce applications today. Recommender systems usually provide the user with a<br>list of recommendations that they might prefer, or supply predictions on how much the user might prefer each item. Choosing what book to<br>read next has always been a question for many. Even for students, deciding which textbook or reference book to read on a topic unknown to<br>them is a big question. There are two common approaches for providing recommendations, they are collaborative filtering and content<br>based filtering. In this report we try to present a model for a personalized recommendation system for books that uses hybrid<br>recommendation approach which is combination of content based and collaborative filtering. The proposed recommendation system tries to<br>learn the user’s preferences and recommends the books to the user based on their preferences. The system also recommends the books to<br>the user based on the user’s demographic parameters like age and location. The system also tries to understand the user’s favourite author<br>and recommends accordingly.</p> ER -