Nowadays, the increasing growth of e-commerce sites i.e. flipkart, amazon, ebay etc. which create ratings, comments and feedback of buyers which lift new application area for recommendation system. Although research on recommendation system has increased significantly over the past 10 years. To help the customer, many e-commerce companies are also developing their recommendation system to help their buyers to choose products more efficiently. The consumer can get advantages by receiving some information about the item which they are likely to buy. Due to this process, the business can get profit with an increasing of its sale. This paper gives some overview of about recommender system and depicts the present patterns of proposal techniques that are for the most part characterized into three classifications: content based, collaborative filtering and hybrid. These paper also describe the challenges of current recommendation method.

Key words: Recommendation system, collaborative filtering, content based filtering, hybrid, Matrix Factorization;