Multi-platform ecommerce application with ai recommendation

Abstract

Electronic commerce or ecommerce is a term for any type of business, or commercial transaction, which involves the transfer of information across the Internet. It covers a range of different types of businesses, from consumer-based retail sites, through auction or music sites, to business exchanges trading goods and services between corporations. It is currently one of the most important aspects of the Internet to appear. Unlike traditional commerce that is carried out physically with effort of a person to go and get products, ecommerce has made it easier for human to reduce physical work and to save time. E-Commerce, which was started in early 1990’s, has taken a great leap in the world of computers. To make the online shopping experience even better, there are a lot of new technologies which include recommendation systems. A recommendation system, or a recommender system, is a subclass of information filtering system that looks to predict the “rating” a user would give to an item, in our case, a product. A recommender system learns from a customer and recommends products that the user will find most valuable from among the available products. Recommendation systems are changing from novelties used by a few E-commerce sites to serious business tools that are reshaping the world of E-commerce. Many of the largest commerce websites are already using recommender systems to help their customers find products to buy, for example: Amazon, eBay, Shoppe, Tiki. In this project, I built an ecommerce application from scratch using React, React Native and Nodejs. Then applying Machine Learning in building a practical Recommendation System AI which gives the user recommendations in real time.