Personalization Using Recommendation Systems: State-of-the Art Review

In the era of internet, the proliferation of services will be a great challenge to the users in selecting the best and optimal services that suit the user requirement. So there is a need to filter, prioritize and efficiently deliver relevant information according to the user requirement. Recommendation systems rescue the users by selecting the required content after searching through large volumes of services. Recommendation system predicts user responses to options using diverse prediction techniques like content-based system, collaborative filtering system and hybrid system. This paper, in detail, explores different characteristics, approaches, evaluation metrics and potentials of different prediction techniques in recommendation systems that endorse the quality of services for the users.