Canteen Recommendation System Based on SpringBoot and SpringAI

Abstract

This paper presents the design and implementation of a university canteen personalized recommendation system based on SpringBoot and SpringAI. The system adopts a front-end/back-end separation architecture. The backend integrates SpringBoot, MyBatis and a MySQL database, while the frontend is built with Bootstrap to provide a responsive interface. By incorporating large language model capabilities via the SpringAI module, the system supports intelligent dish recommendations and conversational management. Through user profiling, dynamic recommendation algorithms, and multi-canteen switching functionality, the system effectively enhances the intelligence and user experience of campus catering services. This paper describes the system architecture, database modeling, AI integration strategy and core implementation in detail, offering a feasible technical path and practical reference for developing smart catering systems in universities.