Recommender Systems in E-commerce and their Challenges

With the advancement in technology and the usage of internet, everything is just a click away from purchasing. It can be online shopping, banking, communicating or even watching movies. Many large e-commerce websites like Amazon and Netflix have already incorporated recommender systems to increase their sales. The competition for providing the best products and services is evident between e-commerce websites. In this paper we have discussed about the common recommendation techniques that are being used in the electronic commerce industry to help customize recommendations. We also discuss ways in which the recommender system enhances the e-commerce business. The paper has also thrown light on the prominent issues and challenges the system faces which includes sparsity and latency. It also proposes areas in which the recommender system needs to be improved so as to give optimal suggestions and tackle with the problems of future.