基于用户画像的智慧图书馆文献资源个性化推荐方法研究
Research on Personalized Recommendation Method for Literature Resources in Smart Libraries Based on User Profile
张峰涛1
作者信息
- 1. 太原市图书馆,山西 太原 030024
- 折叠
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.
Abstract
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.
关键词
用户画像/文献资源/推荐/个性化/智慧图书馆Key words
user profile/literature resources/recommendation/personalization/smart library引用本文复制引用
出版年
2024
NETL
NSTL
万方数据