Efficient tag based personalised collaborative movie reccommendation system

Abstract

Recommender System is a set of programs and techniques used for predicting items or rating of items in fields in which a user may be interested. The objectives of recommendation techniques are to assess and mitigate the problem of information overload where a user is not able to receive a clear result of his search. From these recommendations may help in various decision-making processes such as which items to buy, which music to listen, or which online news to read and which research paper to read etc. In this paper, we introduce a new recommendation model which takes into consideration a user's information based on tagging. The proposed approach offers significant advantages in terms of improving the recommendation quality for movies.