Research on the Construction of the Service System of Smart Libraries in Higher Vocational Colleges Driven by Artificial Intelligence

With the continuous iterative improvement of artificial intelligence, libraries in colleges and universities are accelerating their transformation into intelligence. Taking a higher vocational health college as an empirical object, this study systematically explores the construction path of an intelligent library service system supported by AI technology. Through a combination of quantitative analysis and case study, this study analyses the shortcomings of libraries in higher vocational health colleges in terms of resource management, service mode, and space utilization. It also introduces deep learning algorithms, knowledge graph technology and spatial optimisation models, and proposes a strategy for building a multi-level service system. The results of the study show that a personalised recommendation system based on collaborative filtering algorithms can increase the utilisation rate of library resources in higher education institutions to 28.5%; the space layout optimised by a dynamic planning model can increase the seat turnover rate by 42%; and the response time of an intelligent consultancy service based on an LSTM network is reduced to 1.2 seconds. In addition, this study developed a decision tree model for resource acquisition (with an accuracy of 92.3%) and a formula for assessing user satisfaction (R²=0.87), which provide theoretical support and practical models for the intelligent transformation of university libraries.