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Japanese teaching quality satisfaction analysis with improved apriori algorithms under cloud computing platform

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成果类型:
期刊论文
作者:
Cai, Lini*
通讯作者:
Cai, Lini
作者机构:
[Cai, Lini] Hunan City Univ, Yiyang 413000, Hunan, Peoples R China.
通讯机构:
[Cai, Lini] H
Hunan City Univ, Yiyang 413000, Hunan, Peoples R China.
语种:
英文
关键词:
Improved Apriori Algorithm;Japanese Teaching Quality Evaluation;Relevance Analysis;Satisfaction Model
期刊:
Computer Systems Science and Engineering
ISSN:
0267-6192
年:
2020
卷:
35
期:
3
页码:
183-189
机构署名:
本校为第一且通讯机构
摘要:
In this paper, we use modern education concept and satisfaction theory to study the construction of a system used to evaluate Japanese teaching quality based on a satisfaction model. We use a cloud computing platform to mine the rules of Japanese teaching quality satisfaction by using an improved Apriori algorithm to explore the impact of measurement indicators of teaching objectives, processes and results on overall satisfaction with Japanese teaching practices, so as to improve Japanese teaching in the future. Scientific decision-making, impr...

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