智慧校园中基于大数据的学生课程推荐系统设计

Design of Student Course Recommendation System Based on Big Data in Smart Campus

为应对日益复杂的学习环境和多样化的学科要求,文章设计了基于大数据的学生课程推荐系统。该系统包括服务层、推荐算法层和画像构建层。其中,服务层包括课程推荐结果可视化、课程画像可视化、在线教育平台;推荐算法层采用基于画像的方法,全面考虑学生个性和学科特性;画像构建层通过多源数据分析构建学生和课程画像。另外,为提升推荐准确性,文章提出了基于余弦相似度的改进理论,引入权重调整、特征衰减和动态相似度计算等。

In order to cope with the increasingly complex learning environment and diversified subject requirements,the paper designs a student course recommendation system based on big data.The system includes a service layer,a recommendation algorithm layer and a profile construction layer.Among them,the service layer includes course recommendation results visualization,course portrait visualization,online education platform;the recommendation algorithm layer adopts a profile-based method to fully consider student personality and subject characteristics;the profile construction layer uses multiple source data analysis builds student and course profiles.In addition,in order to improve the recommendation accuracy,this paper proposes an improved theory based on cosine similarity,including weight adjustment,feature attenuation and dynamic similarity calculation.