MCRS: A Course Recommendation System for MOOCs

被引：0

作者：

Huang, Tao ^{[1
]}

Zhan, Gaoqiang ^{[1
]}

Zhang, Hao ^{[1
]}

Yang, Heng ^{[1
]}

机构：

[1] Cent China Normal Univ, Natl Engn Res Ctr E Learning, Wuhan, Hubei, Peoples R China

来源：

PROCEEDINGS OF THE 2017 INTERNATIONAL CONFERENCE ON ADVANCED TECHNOLOGIES ENHANCING EDUCATION (ICAT2E 2017) | 2017年 / 68卷

关键词：

MOOC; online course; big data; course recommendation; Apriori; Hadoop; Spark;

D O I：

暂无

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

With the popularization of MOOC platform, there is a tendency of big data in the number of online courses. Efficient and appropriate course recommendation can improve learning efficiency. According to the characteristics of MOOC platform, MCRS has made great improvement in course recommendation model and algorithm in this paper. The experimental results proves that MCRS's recommendation algorithm is more efficient than Hadoop Apriori algorithm, and recommend appropriate course to user. It turns out that MCRS is more suitable for MOOC platform.

引用

页码：82 / 85

页数：4

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