A study on Recommender Systems and its different approaches

Abstract

Recommender Systems” is an emerging technology that helps customers to find products of their interest. A recommender engine gives personalized suggestions of products by extracting knowledge from the previous users’ interactions to compute predictions [1].  The vast and ever increasing amount of items available on the websites has led to the development of many technologies providing a way to one of them, recommender systems. Many of the onlinetrading websites are already using recommender systems to help their customers find products of their interest[2]. In this paper, we present an explanation of how recommender system helps customers to find the product of their interest through the native Recommender System methods.The native recommender systems methods are classified into three maincategories: content-based filtering, collaborative filtering, and hybrid recommendation approaches