A Survey on Recommender Systems based on Collaborative Filtering Technique

Nowadays Product advertisement and viewer’s choice are two important part of marketing. These two parts generate a system that system is known as Recommender system. Recommender system plays a vital role in internet technology for data gathering and rating up a data. There are four types of filtering technique used in Recommender System-demographic, content, collaborative and hybrid. The most widely and popularly used technique is collaborative filtering. In this paper we describe a little about former three techniques but mainly focuses on collaborative filtering, their types and their major challenges such as cold start problem, data sparsity, scalability, accuracy etc.