Online Shopping System with Prediction Analysis

Abstract

Online shopping is the process whereby consumers directly buy goods, services etc. from a seller interactively in real-time without an intermediary service over the internet. Our system has a special feature that is predictive analysis of each product based on past data analysis. There is two di erent views in this system one is for user and another is for admin. In user view user can see all the products and choose among them. Here we try to implement a clothing system. The system has some categories like Man.Woman,Kids etc. Each category has also some subcategories. In admin view admin can update or delete any data. Admin can see the predictive analysis of each product. The unique feature of our system is the future prediction of each product. Here the prediction works based on the past and present data analysis of each product. Generally in a big system Big Data,Cloud computing etc. used for analyzing the huge number of data. But we have made a small protocol for less amount of data.In the KNN learning algorithm,the decision classi er will detect by itself according to the event and data. But in our small protocol we will build a system with static classi er,we will take the decision according to the static range.