Video Rental Recommendation System by Using Collaborative Filtering Method

Abstract

Collaborative filtering works to aggregate ratings or preferences on items; discovers user profiles learning from user’s historic rating record; generates a new recommendation on a basis of inter-pattern comparison. Recommendation system is based on collaborative filtering method. Collaborative filtering based on a prediction for a user should be based on the similarity between the interest profile of that user and those of other users. In this paper, video recommendation system is developed by using Collaborative filtering method. Recommendation system is subdivided into three main parts. First, collect data for movies. Second, search movie by top-ten or by actor or by title or by director. Next, recommend to the user by using recommendation system.