Machine Learning Techniques for Book Recommendation: An Overview

Abstract

Recommender Systems are intelligent systems which are used as an expert in making decisions in real life problems. They have replicated the human experts and positively affected the e-commerce by changing the behavior of customers and sellers. Book Recommender Systems (BRS) help the librarians in the management of library catalog efficiently. It supports the readers in choosing the best book for them. Merchants implement the BRS to manage their inventory and gain more profit. In this paper, we have discussed traditional techniques of recommendation, machine learning techniques and their categories i.e. supervised, unsupervised, semi-supervised and reinforcement learning. Also, Machine Learning (ML) techniques used for the book recommendation and their effect on book recommender systems have been discussed. The work will help the researchers in exploring new dimension for recommendation technology in general and book recommendation in particular.