BOOK RECOMMENDER SYSTEMS USING COLLABORATIVE FILTERING

Abstract

A book recommendation system is a tool that suggests books to users based on their reading history, thereby showing the user's reading preferences. The book recommendation system helps customers have more experience with different book products such as genre, writing style, and author and helps users discover new books that they may love. This thesis proposes a book recommendation system model using collaborative filtering, the principle behind the collaborative filtering process is to recommend items to users by identifying users or items with similar interests, based on their previous choices. In other words, it tries to find users with similar interests and recommend books to those similar users. I tested on the Books dataset. The results show that the book recommendation system has provided accurate suggestions to users. Specifically, Precision is, recall of collaborative filtering is ...., compared to content based is superior.