Article
ONEKART: AN E-COMMERCE PLATFORM
The rapid growth of online shopping platforms and digital marketplaces has significantly increased the need for intelligent recommendation systems capable of improving user experience and customer satisfaction. Traditional e-commerce platforms often struggle to provide personalized product recommendations based on user interests, browsing behavior, and purchase history. This paper presents the design and implementation of ONEKART, an AI-based E-Commerce Recommendation Platform developed to provide personalized product suggestions using user preferences and hybrid recommendation techniques. The proposed system integrates content-based filtering, collaborative filtering, and intelligent recommendation mechanisms to improve product discovery and customer engagement. The platform is designed using modern web technologies including React.js, Tailwind CSS, Node.js, Express.js, MongoDB, and RESTful APIs to ensure scalability, responsiveness, and secure communication. ONEKART provides features such as user authentication, product management, shopping cart functionality, order tracking, AI-based recommendations, secure payment integration, and admin management. The implementation demonstrates improved recommendation accuracy, better user engagement, and enhanced shopping experiences compared to traditional static e-commerce systems. The proposed platform provides a scalable foundation for future intelligent e-commerce applications.
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