Bookshelf: A Book Recommendation System Using Collaborative Filtering

Bookshelf: A Book Recommendation System Using Collaborative Filtering

Nancy Taswala, Anish Kamble, Sana Khan
***

Abstract – In the huge amount of literature, finding the perfect book to please your literary thirst can be a task. With countless genres, authors, and styles to choose from, it's easy to be lost in a sea of literacy. Fortunately, we live where technology and data can come to our rescue, guiding us toward our next great read. In this paper, we present the algorithms used to create Bookshelf and how we tried several algorithms before using collaborative filtering. Next, we discussed how the whole system is designed. The objective of a book recommender system is to create a personalized and engaging experience for book lovers, by providing them with relevant and interesting book recommendations that match their unique preferences and interests.

Overall, the objective of bookshelf is to create a win-win situation by providing users with personalized recommendations that enhance their reading experience.

Key Words: Recommender System, Collaborative Filtering, Cosine Similarity.