International Science Community Association Research Journal of Computer and Information Technology Sciences 2320 – 6527 5 4 2017 06 20 Future of next generation recommender systems 9 12 EN Swati Dewangan 1 Bhilai Institute of Technology, Durg (CG), India S.D. Mishra 2 Department of Computer Science and Engineering, Bhilai Institute of Technology, Durg (CG), India Jyoti Upadhyay 1 AISECT University, Bhopal, MP, India Pratima Gautam 2 AISECT University, Bhopal, MP, India Monika Verma 1 Department of Computer Science & Engg., BIT Durg, (CG), India Arpana Rawal 2 Department of Computer Science & Engg., BIT Durg, (CG), India > Short Review Paper 2017 4 10 2017 06 20 With so many overwhelming information filtering-cum-accessing options from the Web, there is a need to sort, prioritize and offer relevant information efficiently in order to alleviate the problem of information overload. Till date, the exhaustive survey on recommender systems have unfolded their various contextual components like design types, filtering approaches, recommendation criteria, evaluation metrics, performance metrics and deployed application domains. Recommender systems have been reported to apply machine learning algorithms in evolutionary ladder on information, products and services of users’ interest among the tremendous amount of available items. In this paper, we discuss various approaches used to build recommender systems, recommender system classification hierarchies as well as comparative interpretation among them. Copyright@ International Science Community Association