Abstract

The Online Chatbot-Based Ticketing System is designed to enhance user experience and streamline the process of booking tickets for various events, services, and travel. Traditional ticketing systems often involve lengthy processes, leading to user frustration and inefficiencies. This system leverages advanced chatbot technology to provide a conversational interface that allows users to interact seamlessly with the ticketing platform. The core functionalities of the system include real-time ticket booking, event inquiries, payment processing, and support for user queries through a natural language interface. By utilizing machine learning algorithms and natural language processing, the chatbot is equipped to understand user intents and provide personalized responses, facilitating a user-friendly interaction. This dissertation discusses the design and implementation of the system, highlighting its architecture, user interface, and backend integration with payment gateways and databases. A series of usability tests and case studies are conducted to evaluate the system's effectiveness in real-world scenarios, measuring user satisfaction and efficiency gains compared to traditional methods. The findings demonstrate that the Online Chatbot-Based Ticketing System significantly reduces the time required for ticket purchasing while enhancing user engagement and satisfaction. This research contributes to the growing field of AI-driven solutions in the ticketing industry, showcasing the potential for automation to improve operational efficiency and customer experience