ORBIT: Hybrid movie recommendation engine

Today, users will get so many movie recommendations websites, which suggest users best movies according to their interests. All these websites have implemented one of the conventional content, context and collaborative recommendations algorithms. Alone, these algorithms are failed 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 ORBIT, which is a movie recommendation engine, based on a unique Hybrid recommendation algorithm, satisfies a user by providing best and efficient books recommendations. Comparative case study of conventional recommendation algorithms to ORBIT's Hybrid movie recommendation algorithm has also been studied and presented in this paper. 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 ORBIT.