Comparative Analysis of Techniques Used in Book-based Recommender System

Recommender system has become a very important tool to accelerate businesses’ growth by recommending suitable products to customers. However, in general public, their basic knowledge regarding recommender system still needs to be improved. Besides, the understanding on types of recommender systems and which type of recommender system performed the best need to be studied more in depth. Hence, this paper aims to study the existing techniques in recommender systems and evaluate their accuracy on predicting an item's rating. The chosen techniques will be implemented in the prototype using Python. With the help of graphical user interface, the result can be visualized in better manner. The results obtained from this paper will be able to prove or deny existing theory made on the techniques. Besides, commercial company would be able to have an insight on which type of recommender system that should be implemented.