In the social networking era, product reviews have a significant influence on the purchase decisions of customers so the market has recognized this problem The problem with this is that the customers do not know how these systems work which results in trust issues. Therefore a different system is needed that helps customers with their need to process the information in product reviews. There are different approaches and algorithms of data filtering and recommendation. Most existing recommender systems were developed for commercial domains with millions of users. In this paper we have discussed the recommendation system and its related research and implemented different techniques of the recommender system.