基于协调过滤技术的高校学习资源个性推荐系统实证研究  

An empirical study on the personalized recommendation system of college learning resources based on collaborative filtering technology

作　　者：林丽金[1] 李文翔[1] 杨俊贤[1] 李忠森[1] 

机构地区：[1]福建对外经济贸易职业技术学院信息技术系,福建福州350016

出　　处：《宁德师范学院学报（自然科学版）》2016年第1期67-70,共4页Journal of Ningde Normal University(Natural Science)

基　　金：2013年福建省教育厅A类科技项目(JA13405)

摘　　要：针对高校学习资源信息过剩而无法向学习者进行个性推荐资源的问题,并鉴于电子商务个性化推荐模型研究的启示,文章尝试应用某高校学生2014年的借阅学习资源数据,应用协同过滤技术构建学习资源个性化推荐系统模型,并根据实证结果,对读者进行学习资源推荐,从而提高学习资源搜索和借阅效率.Because of the surplus of learning resources in colleges and universities, it is impossible to make a personalized recommendation to the learners. In the enlightenment of the personalized recommendation model of e-commerce, and the study of learners＇ borrowing of learning resources in a certain university in 2014, a collaborative filtering technology is used to build a model of personalized recommendation system. According to the empirical results, learning resources are recommended for the readers so as to improve the efficiency of resource searching and borrowing.

关 键 词：学习资源 协同过滤 个性推荐 

分 类 号：TP391.3[自动化与计算机技术—计算机应用技术]