Techniques of recommender system

Abstract

The term Recommender system is described as any organization that provides personalized suggestions as a result and it effects the user in the individualized way to favorable items from the large number of opinions. The voluminous inflation of the reachable data online and also the number of users have lead to the information overload problem. To overcome this problem the recommender system came into play as it is able to prioritize and personalize the data. Recommendation systems have developed alongside with the net. Recommender system has mainly three data filtering methods such as content based filtering technique, collaborative based filtering technique and the hybrid approach to manage the data overload problem and to recommends the items to the user the items they are interested in from the dynamically generated data. This paper makes a comprehensive introduction to the recommender system with its types, content based filtering, collaborative filtering and the hybrid recommendation.