ABSTRACT
This chapter presents a movie recommender system, which employs the average ratings of the users to analyze and predict the value of a particular movie. It also presents a reliable recommendation system, which is better than the other existing approaches in terms of accuracy and time complexity. Recommendation system can be made further accurate by using content-based filtering, which takes a number of parameters to recommend the product to the user and not just the rating. The recommendation system is a subpart of the information filtering system, which aims to facilitate users by presenting them products related to their choices by predicting the "rating". Recommender systems make predictions based on one of the two methodologies such as content-based filtering or collaborative filtering. An intelligent recommender system was presented in which the author used fuzzy cognitive maps. Trust is another important factor, which plays a significant role in recommendations.
