Intelligent learning system based on personalized recommendation technology

被引:34
|
作者
Li, Hui [1 ,2 ]
Li, Haining [3 ]
Zhang, Shu [4 ]
Zhong, Zhaoman [1 ]
Cheng, Jiang [3 ]
机构
[1] Huaihai Inst Technol, Dept Comp Sci, Lianyungang, Jiangsu, Peoples R China
[2] Marine Resources Dev Inst Jiangsu, Lianyungang, Jiangsu, Peoples R China
[3] Ningxia Med Univ, Gen Hosp, Ningxia Key Lab Cerebrocranial Dis, Dept Neurol,Incubat Base,Natl Key Lab, Yinchuan, Peoples R China
[4] Huaihai Inst Technol, Business Sch, Lianyungang, Jiangsu, Peoples R China
来源
NEURAL COMPUTING & APPLICATIONS | 2019年 / 31卷 / 09期
关键词
Smart education; Learning resource; Collaborative filtering; SVM; SEMANTIC CONTEXT; ALGORITHM;
D O I
10.1007/s00521-018-3510-5
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the continuous development of networks, web-based e-learning is changing the way people acquire knowledge. An increasing number of learners are eager to acquire more knowledge through personalized and intelligent means. Based on content recommendation and collaborative filtering recommendation algorithm, this paper proposes a hybrid recommendation algorithm which can improve the efficiency of traditional recommendation algorithm. The presented research introduces the whole process of user interest model and teaching resources model, which also designs and implements the personalized network teaching resources system prototype. Finally, in comparison with the traditional recommendation algorithm, the improved hybrid recommendation algorithm has more advantages in personalized intelligent educational resources recommendation system.
引用
收藏
页码:4455 / 4462
页数:8
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