基于协同过滤的网络学习个性化推荐技术研究  

The Research on Personalized Recommendation Technology Based on Collaborative Filtering in E-learning

作　　者：于丽梅[1] 李艳萍[1] 高金乔[1] 

机构地区：[1]河北工业大学廊坊分校,河北廊坊065000

出　　处：《廊坊师范学院学报（自然科学版）》2015年第5期31-36,共6页Journal of Langfang Normal University(Natural Science Edition)

基　　金：河北省教育厅科学研究项目"改进的协同过滤算法在网络学习中个性化关联推荐的应用研究"(ZD20131070)

摘　　要：随着计算机网络技术的快速发展,学习网站上的信息量与日俱增,用户在大量的学习资料中想找到自己需求的资料也越来越难。文章提出了基于用户隐式特征的协同过滤算法,通过对网络学习数据进行算法测试,准确率高于K-means等其他推荐算法。With the rapid development of computer network technology, the amount of information on the learning network is various and increasing. Users often feel more and more difficult to find their own demand from learning materials on the Internet. This paper puts forward the collaborative filtering algorithm based on user implicit characteristics. By the algorithm tested for E-learning data, the accuracy is higher than K-means and other recommendation algorithm.

关 键 词：协同过滤 精确度 隐式特征 稀疏性 网络学习 

分 类 号：G642[文化科学—高等教育学]