基于深度学习的图书馆文献推荐系统设计  

Design of Library Literature Recommendation System Based on Deep Learning

作　　者：曹艺潇[1] CAO Yixiao(The Library of Wuhan University of Science and Technology,Wuhan Hubei 430081,China)

机构地区：[1]武汉科技大学图书馆,湖北武汉430081

出　　处：《信息与电脑》2025年第1期14-16,共3页Information & Computer

基　　金：2023年湖北省高校图工委一般项目“基于大数据技术的高校图书馆虚拟参考咨询的技术与实践”(项目编号:2023-YB-21)。

摘　　要：深度学习技术以其强大的数据处理能力,为个性化推荐提供了新的解决方案。文章介绍了基于深度学习的图书馆文献推荐系统的设计与实现。该系统集成了用户行为分析、文献特征提取和精准推荐生成等功能,旨在提供高效、准确的文献推荐服务。研究通过功能测试和压力测试对系统进行了评估,结果验证了系统的稳定性和可靠性。Deep learning technology provides a new solution for personalized recommendation with its powerful data processing capabilities.The article introduces the design and implementation of a library literature recommendation system based on deep learning.The system integrates functions such as user behavior analysis,literature feature extraction,and precise recommendation generation,aiming to provide efficient and accurate literature recommendation services.The system was evaluated through functional testing and stress testing,and the results verified its stability and reliability.

关 键 词：深度学习 图书馆 文献推荐 数据处理 

分 类 号：G25[文化科学—图书馆学]