Library Literature Data Resource Retrieval and Intelligent Recommendation Network System Based on Cloud Computing

Abstract

With the rapid development of information technology, as the core institution of knowledge storage and dissemination, libraries are facing the challenge of how to efficiently manage huge literature data resources and improve user retrieval experience. The purpose of this study is to build an advanced system to optimize the retrieval efficiency of literature data resources and improve retrieval accuracy and speed through the powerful data processing and storage capabilities of cloud computing. At the same time, the system will have an intelligent recommendation function, which will accurately push literature resources that meet the needs of users according to multi-dimensional factors such as user behaviour and preferences, improve user experience, enhance the utilization value and service quality of library literature resources, and promote the digital construction of libraries. The experimental data show that when processing large-scale literature data, the retrieval efficiency of this system is improved by 45%, and the intelligent recommendation accuracy rate reaches 92%, which is significantly better than the traditional retrieval system. This research result provides new ideas and practical cases for the digital transformation of libraries and is expected to further promote the intelligent and personalized development of library services.