PRODUCT RECOMMENDATION SYSTEM USING MACHINE LEARNING THROUGH BIG DATA IN E-COMMERCE WEBSITE

This paper presents the design and implementation of a recommendation system in e-commerce website using machine learning. A recommendation system is a system that is based on an analysis of product purchases, customer demographics, and buy history.Recommendation activities are common in our daily lives, owing to the many products and methods of recommendation, as well as activities in various forms, such as supermarkets and shopping. A type of recommendation system is the purchasing guide, which recommends users’ preferred products and increases sales.The aim to design a recommendation system is to make information environments for the users. One of the most common and easily understandable applications of big data is the recommender systems. Users will be able to search through data records that are relevant to their interests and preferences using this system.Machine learning will help recommended engine so that customers easily find their desire product. E-commerce sites employ recommender systems to make product recommendations to their clients. Products are frequently recommended based on the top overall sellers on a website, as well as the client’s demographics. Products can also be recommended based on an analysis of a customer’s previous purchasing behavior as a predictor of future purchasing behavior.