Abstract

The massive growth of internet in the past decade has lead to the birth of many E-Commerce websites and applications. More and more people prefer shopping online rather than going to retail stores. The main idea of online shopping is to ease the shopping experience by getting personalized recommendations of products. This is also what the E-Commerce websites are expected to do. The present recommendation system is ineffective because it doesn't handle three main problems: Limited resource, cold start and data valid time. The recommendation system consists of user model, recommended model and recommendation algorithm. This paper includes the proposed model that focuses on the improvement to the recommendation algorithm by providing solutions to limited resource and cold start problem. The proposed system aims at better customer satisfaction.