一种数字图书馆资源聚合质量推荐模型  

An aggregation quality recommendation model for digital library resources

作　　者：张艳[1] ZHANG Yan(Xi’an Foreign Affairs University,Xi’an 710077,China)

机构地区：[1]西安外事学院,西安710077

出　　处：《信息技术》2021年第8期87-91,共5页Information Technology

基　　金：陕西省图书馆学会2019年度研究课题(191037)。

摘　　要：为提高数字图书馆资源聚合推荐服务质量,在研究了推荐系统中常用的二元模糊语言基础上,设计了一种数字图书馆资源聚合质量推荐模型。模型考虑了用户的模糊偏好,并将偏好建立在二元模糊语言模型中。同时,设计并实现了一种混合推荐策略,可在基于内容的推荐方法和协作推荐方法之间进行切换。通过仿真分析,结果表明文中所提方法由于考虑推荐时的质量,算法整体性能优于传统基于内容和协作的推荐方法。In order to improve the quality of digital library resource aggregation recommendation service,this paper designs a digital library resource aggregation quality recommendation model based on the research of binary fuzzy language which is commonly used in the recommendation system.The model considers the user’s fuzzy preference,and establishes in the binary fuzzy language model using the preference.At the same time,a hybrid recommendation strategy is designed and implemented,which can switch between content-based recommendation method and collaborative recommendation method.The simulation results show that the overall performance of the proposed algorithm is better than that of the traditional content-based and collaborative recommendation methods because of the quality of recommendation.

关 键 词：数字图书馆 资源聚合 质量推荐 二元模糊语言 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]