Research Gaps in Recommendation Systems

It has become challenging to find relevant information needed for the user. In this evolving world of technology finding relevant data has become very crucial as most of the businesses revolve around data. To solve this problem, recommender systems are used. It has become very difficult to get relevant data without any proper recommender systems. Today, in every field recommender systems are used to provide relevant data to user on the basis of their choices, needs or interests. Content based recommender system and collaborative filtering recommender systems are two basics types of recommender systems are available. These two systems can be combined to make recommender system more efficient, these combined systems are called hybrid systems. The purpose of the paper is to help new researchers to understand the working of basic recommender systems and identifies new research area for further improvement of recommender system.