摘要
该文针对现有推荐方法推荐准确率过低的问题,开展智慧图书馆文献资源个性化推荐方法设计研究。先通过用户画像的应用,构建用户兴趣特征模型。然后提取文献资源特征,实现文献资源特征与用户兴趣特征的匹配,实现文献资源个性化推荐。最后应用对比实验证明所提方法的先进性。实验结果证明,新的推荐方法可有效促进文献资源推荐准确率的提升,应用效果较好。
This article focuses on the problem of low recommendation accuracy in existing recommendation methods,and conducts research on the design of personalized recommendation methods for literature resources in smart libraries.Firstly,construct a user interest feature model through the application of user profiling.Then extract the features of literature resources,match them with user interest features,and achieve personalized recommendation of literature resources.Finally,comparative experiments are carried out to prove the progressiveness of the proposed method.The experimental results show that the new recommendation method can effectively promote the improvement of accuracy in literature resource recommendation,and the application effect is good.
作者
张峰涛
ZHANG Fengtao(Taiyuan Library,Taiyuan 030024,China)
出处
《数字通信世界》
2024年第7期34-36,共3页
Digital Communication World
关键词
用户画像
文献资源
推荐
个性化
智慧图书馆
user profile
literature resources
recommendation
personalization
smart library
作者简介
张峰涛(1978-),男,汉族,河南舞阳人,副研究员馆员,本科,研究方向为图书馆学。
