NOVA: Hybrid book recommendation engine

Now days, there are so many book purchasing websites available, claim to recommend users best books according to their interests. Most of the recommendations are based on conventional content, context and collaborative recommendations algorithms. All these algorithms alone fail to recommend best and efficient recommendations to user. So, there is a need to evolve a unique algorithm which combines the features of conventional algorithm along with its new features. This paper describes the NOVA, which is a book recommendation engine, based on a unique Hybrid recommendation algorithm, satisfies a user by providing best and efficient books recommendations. This paper also presents a comparative case study of conventional recommendation algorithms to NOVA´s Hybrid books recommendation algorithm. This case study is based on evaluating criteria of recommendation algorithm i.e. accuracy, precision, recall, F-measure etc. Results of this case study are represented in the form of tables and graphs to clearly specify the need of NOVA.