Online Ecommerce Hypermarket Shopping site with Product Recommendation System, Prediction based System by Machine Learning, Internet Security and Artificial Intelligence

In this paper, an e-commerce website with Content-based Recommendations and collaborative filtering recommender systems is proposed. The Recommender system makes use of data mining and information filtering techniques to make sure that the customer has been recommended a product based on his/her choice. The Collaborative Filtering works on similar likes of different users and recommends the products accordingly. It checks if two users have similar tastes and if 1 user has liked a specific product, so it recommends the same to the other. The Content-based Recommendations recommend items with similar metadata tags. The proposed website makes use of both the algorithms to provide the user with ease of navigating and saves their time as well. It makes use of an Artificial Intelligence bot for support to acknowledge the queries of the users and provide them with a solution to their problems. The Payment Gateway system is fully secured with SSL/TLS to enable fast and secure transactions. To strengthen the security more, the IP Lookup checks if it's a spy or if someone is trying to gain access illegally. It also shows the IP address of all the Active People on the website. For the fast delivery, we have made use of an Automated Shipping Estimator based on Zon. Thus the website is secured helps the users to probe deeper into their shopping needs and order within less time the products they require.