Research on the Impact of ChatGPT and Other NLP Technologies Based on GPT Models on the Construction and Development of Intelligent Libraries in Higher Education

Abstract

This paper delves into the profound impact of NLP technology based on GPT model on the construction and development of intelligent libraries in higher education. The article firstly analyses the current development trend of intelligent libraries in higher education, and then elaborates the application practice of GPT model in key areas such as dialogue interaction, personalized resource recommendation, information processing and metadata management in libraries. Despite the benefits, challenges such as privacy concerns, semantic understanding limitations, domain-specific corpus requirements, and various user needs present obstacles. To address these, this research work proposes a comprehensive architecture incorporating secure data handling, optimized GPT model training, cross-domain knowledge integration, and user-friendly interfaces. Experimental testing of this architecture with university participants demonstrated a 66% reduction in query response times and a 21% increase in user satisfaction scores compared to traditional systems. These findings indicate significant improvements in accessibility, personalization, and operational efficiency. However, challenges related to data privacy and semantic accuracy were also identified. The proposed framework aims to utilize the capabilities of ChatGPT to enhance service efficiency, user satisfaction, and data management in intelligent libraries which support the evolving needs of students and educators.

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