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Research of personalized course recommended algorithm based on the hybrid recommendation

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成果类型:
期刊论文、会议论文
作者:
Qing Yang;Peiling Yuan;Xi Zhu
作者机构:
Department of Computer, Central China Normal University, Wuhan,China
TCL Yunchuang Technology Co., Ltd., Guangdong, China
语种:
英文
关键词:
Association rules;Intelligent materials;Manufacture;Students;Cold start;Collaborative filtering algorithms;Data sparsity;Elective course;Hybrid algorithms;Hybrid recommendation;Personalized course;Recommendation algorithms;Collaborative filtering
期刊:
MATEC Web of Conferences
ISSN:
2261-236X
年:
2018
卷:
173
页码:
03067
会议名称:
2018 International Conference on Smart Materials, Intelligent Manufacturing and Automation, SMIMA 2018
会议时间:
24 May 2018 through 26 May 2018
出版者:
EDP Sciences
机构署名:
本校为第一机构
院系归属:
计算机学院
摘要:
This paper presents a personalized course recommended algorithm based on the hybrid recommendation. The recommendation algorithm uses the improved NewApriori algorithm to implements the association rule recommendation, and the user-based collaborative filtering algorithm is the main part of the algorithm. The hybrid algorithm adds the weight to the recommendation result of the user-based collaborative filtering and association rule recommendation, implementing a hybrid recommendation algorithm based on both of them. It has solved the problem of...

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