Modern Recommendation System for Big Data Based E-Commerces Platform

Abstract

An Ecommerce website is known as the platform where selling and buying product, services, activities over the internet. Ecommerce system has already ruled the entrepreneur world in current trends. Whenever people want to sell or buy the products, they only need to register and simply do the selection of items and do the transactions over the internet. Most people prefer to purchase the products that they want on online because it is more efficient and reliable to the customers. The recommendation system will identify the products based on the customers’ behavior pattern, preference, psychology, current trends and so on. The purpose of the algorithm is to make the ecommerce system work efficiently so that the when the customer is surfing the website, the algorithm will determine the set of products or services for the customer automatically connecting to the database and it will show the similarities of the products that users has been search for. Or, the system thinks that these set of products are better for him. Besides, the recommendation system will run in the background even someone is new to the system while it was being used. Also, a common problem that customers always face is the network page loading delay, network delay, jitter, etc when there are more users are on that site. These problems will be identified by using network monitoring tools and the proposed system will detect it in efficient way. The system admin will be able to see instantly the current usage pattern of the said website.