Abstract: With the rapid advancement of large language models (LLMs), there is growing potential for their integration into the intelligent information processing of ancient books. This study seeks to bridge the gap between LLMs and the field of ancient books processing, enhancing the theoretical and technical foundations of the information resource management discipline. Drawing on a coding-based deconstruction method, this study analyzed interviews from 28 domain experts to identify the key factors necessary for effective integration. The analysis reveals a comprehensive framework that centers on four critical dimensions: policy, technology, ancient books, and users. Building on this framework, this study proposes a set of practical paths tailored to the unique demands of the discipline. The findings suggest that these four dimensions are essential to the successful application of LLMs in the domain. Finally, this study offers detailed strategies for implementation across theoretical, technical, and user service, providing a roadmap for future development in this emerging field.

Key words: Large language model, Artificial intelligence generative content, Technology resilience, Ancient books intelligent information processing, Framework system, Practical path