Smart Event Booking System with Personalized Recommendations

This study introduces a highly secure, personalized, and scalable event-booking system whose scope is to modernize the idea of event discovery and booking and overall management. On leveraging a support vector machine-based algorithm, personalized suggestions are provided toward events based upon users own booking history with enhanced engagement in addition to consumer satisfaction. The front-end, developed using React, gives a dynamic and interactive interface displaying event details, including name, organizer, venue, time, and pricing. It also enables users to choose seats interactively with real-time updates of pricing and integrates seamlessly into a secure payment process by using Express.js. For event organizers, the system provides an intuitive dashboard that helps manage event attributes such as type, venue, date, and pricing efficiently. To ensure robust security and data privacy, all user information is encrypted using bcrypt.js, while event-related data is securely stored in an PostgreSQL database. The backend, built with Node.js and Express.js, is designed to handle high scalability and efficiency, supporting smooth operations for both attendees and event organizers. The system, through the integration of machine learning-based personalized recommendations and dynamic user interfaces, addresses the key challenges in event management and booking. It streamlines administrative tasks, enhances user experiences, and provides a reliable and comprehensive platform for event organizers and attendees alike.