E-commerce Recommendation System with Reverse Image Search

Abstract

The business-to-consumer(B2C) part of Electronic commerce (e-commerce) is the most prominent and wide use of business over the World Wide Web. The essential objective of an e-commerce website is to sell goods and services online. This project deals with developing an e-commerce website for Sale of Different types of products categorized under similar features. In order to facilitate online purchase User Accounts and Guest Accounts are provided to the user. Our system is implemented using a 3-tier approach, web browser as our front-end client, Node web server as a middle tier and with a backend database (MongoDB). This project allows viewing various products available and tagging them, enables registered and Guest users to purchase desired products instantly via different payment platforms (Stripe Payment) or COD (Cash on Delivery). Our Website also helps users, either Registered or Guest, to search products accurately by using Machine Learning Techniques like Text analysis, Text sentiment analysis, Computer Vision and Deep Learning. Many unique features are also added in the project like Searching products by image using reverse image search, User can tag products to get updates on related products and every product will have a consumer blog where product related issues can be discussed