Movie Recommendation Using Vectorisation

Abstract

In todays busy world, entertainment has become a necessity for everyone to refresh our energy and mood. Entertainment refreshes our mind and makes us confident for work so that we can perform more enthusiastically. For revitalising ourselves, we can either listen to music or can watch movies of our choice. For this, one can make use of Recommendation Systems which are more reliable, since in searching we require more and more time which one cannot afford to waste. Here I have designed a system for Movie Recommendation. Now, to improve the accuracy of a movie recommender, a Hybrid approach by combining collaborative filtering and content based filtering using Support Vector Machine as a classifier is presented in the proposed methodology and comparative results have been shown which depicts that the proposed approach shows an improvement in the accuracy, quality and scalability of the movie recommendation system than the pure approaches in three different datasets. Hybrid approach helps to get the advantages from both the approaches as well as tries to eliminate the drawbacks of both methods.