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Abstract: With the rapid development of information technology, traditional library information management systems are no longer able to meet the needs of modern users for efficient, convenient, and personalized services. We aim to design and implement an artificial intelligence based library information management system to improve the management efficiency and service quality of the library. The system adopts a layered architecture design, including front-end user interface layer, back-end business logic layer, and data storage layer, to ensure high performance, high availability, and high scalability of the system. The functional modules cover user management, book management, intelligent retrieval, and data analysis, to meet the diverse needs of users. By integrating artificial intelligence technologies such as natural language processing, machine learning, and image recognition, the system has achieved functions such as semantic retrieval, personalized recommendation, and multimodal retrieval, significantly enhancing the user experience. During the development process, the agile development process is followed and technology stacks such as Python, Django, MySQL, etc. are used to ensure efficient development and stable operation of the system. The test results show that the system response time can be maintained within 2 seconds under high concurrency conditions, and user satisfaction reaches 85% . This study provides new perspectives and methods for research in the field of library information management, and provides strong technical support for the digital transformation and intelligent upgrading of libraries, which has important theoretical and practical significance.

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