基于协同过滤的个性化推荐选课系统研究  

Research on the Elective System with Personalized Recommendation Based on Collaborative Filtering

作　　者：徐天伟[1,2] 宋雅婷[2] 段崇江[2] 

机构地区：[1]华中科技大学教育科学研究院,湖北武汉430074 [2]云南师范大学信息学院,云南昆明650500

出　　处：《现代教育技术》2014年第6期92-98,共7页Modern Educational Technology

基　　金：国家自然科学基金项目"基于e-Science的民族信息资源融合与语义检索研究"(项目编号:61262071)的研究成果

摘　　要：针对高等学校学生选课系统中存在的缺乏个性化课程推荐、选课效率不高的问题,通过对个性化推荐技术的分析研究,提出了基于项目、用户及属性值矩阵的协同过滤算法,并把该算法应用到选课系统中,数据表明,算法解决了个性化推荐技术中的冷启动问题,相关指标有明显提高,实现了课程的个性化推荐和新课程的推荐。Problems of lacking in individualized curriculum recommendations and inefficiency exist in current course selection systems of institutions of higher education. In allusion to these limitations, this paper presents a novel collaborative filtering algorithm based on the project, user and attribute-value matrix through analysis and study of personalized recommendation technology. The proposed algorithm has been successfully applied to the elective system. Experimental results indicate that the proposed approach can solve cold-start technology in personalized recommendation algorithm, improve the related indicators significantly, and achieve a personalized recommendation and new courses recommendation.

关 键 词：协同过滤 个性化推荐 选课系统 

分 类 号：G40-057[文化科学—教育学原理]