CAJ | 학술논문

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。
침대고등학교학생선과계통중존재적결핍개성화과정추천、선과효솔불고적문제，통과대개성화추천기술적분석연구，제출료기우항목、용호급속성치구진적협동과려산법，병파해산법응용도선과계통중，수거표명，산법해결료개성화추천기술중적랭계동문제，상관지표유명현제고，실현료과정적개성화추천화신과정적추천。
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.