摘要
为解决传统推荐检索平台在实际应用中存在的检索效率低问题,开展基于人工智能的图书馆信息资源推荐检索平台设计研究。对平台框架及检索接口进行设计,构建图书馆信息资源聚合数据库,基于人工智能对图书馆用户偏好值进行计算,在此基础上进行图书馆信息资源推荐,完成图书馆信息资源推荐检索平台设计。实际运行测试结果表明该平台与基于稀缺理论的推荐检索平台相比,检索效率更高,且检索结果能够充分满足用户预期偏好。
In order to solve the problem of low retrieval efficiency existing in the practical application of traditional recommended retrieval platforms,a research on the design of a recommended retrieval platform for library information resources based on artificial intelligence was carried out.Design the platform framework and retrieval interface,build a library information resource aggregation database,calculate library user preference values based on artificial intelligence,and on this basis,carry out library information resource recommendation,complete the library information resource recommendation retrieval platform design.The actual running test shows that compared with the recommended retrieval platform based on the scarcity theory,the retrieval efficiency of the platform is higher,and the retrieval results can fully meet the user’s expected preferences.
作者
吴冬梅
WU Dongmei(Lanzhou University of Arts and Science Library,Lanzhou Gansu 730000,China)
出处
《信息与电脑》
2021年第13期159-161,共3页
Information & Computer
关键词
人工智能
图书馆
信息资源
推荐检索平台
artificial intelligence
library
information resource
recommended retrieval platform
