基于改进的混合模式个性化选课推荐技术研究

摘要

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 im-proved mixed model algorithm based on the content , project and user attribute-value through analysis and study of personalized recommendation technology .The proposed algorithm has been successfully applied to the elective sys -tem.Experimental results indicate that the proposed approach can solve cold -start technology in personalized recom-mendation algorithm , improve the related indicators significantly , achieve a personalized recommendation and new courses recommendation and reduce the blindness by the MACE data sets .%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、 选课效率较低的问题, 通过对个性化推荐技术的分析研究, 提出了基于内容、 项目及用户属性的改进混合模式算法, 并将该算法应用到选课系统中, 用MACE数据集对算法进行验证. 结果表明, 该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, 实现了课程与新课程的个性化推荐, 并减少了选课的盲目性.