改进Apriori算法在老年教育移动平台教学评价中的应用研究

Q4 Decision Sciences
Jun Chen
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引用次数: 0

摘要

如何提高老年教育的教学水平,对当前“老年化”的国家和地区具有重要的现实意义。在本研究中,我们改进了Apriori算法来分析教学评价数据,并对其性能进行了测试和应用。结果表明,传统Apriori算法的最小和最大运行时间分别为23 ms和177 ms,而改进Apriori算法的最小和最大运行时间分别为17 ms和163 ms,在数据挖掘中具有更好的分类性能。通过对教师基本信息的分析,揭示了教师职称、教育程度和年龄之间的关系。与其他算法相比,改进的Apriori算法在一定程度上节省了运行时间,具有比其他算法更好的准确性和精密度,能够实现对高中教育移动平台教学评价数据的有效分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application research of improved Apriori algorithm in teaching evaluation of mobile platform for elderly education
How to improve the teaching level of elderly education is of great practical significance to the current 'elderly' countries and regions. In this study, we improve the Apriori algorithm to analyse the teaching evaluation data, and test the performance and apply the analysis. The results show that the minimum and maximum runtime of the traditional Apriori algorithm is 23 ms and 177 ms respectively, while the minimum and maximum runtime of the improved Apriori algorithm is 17 ms and 163 ms respectively, which indicates a better classification performance in data mining. The basic information of teachers was analysed to show the association of teachers' titles, education and age. Compared with other algorithms, the improved Apriori algorithm saves running time to a certain extent, has better accuracy and precision than other algorithms, and can achieve effective analysis of teaching evaluation data on the mobile platform for senior education.
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来源期刊
International Journal of Networking and Virtual Organisations
International Journal of Networking and Virtual Organisations Decision Sciences-Information Systems and Management
CiteScore
1.40
自引率
0.00%
发文量
25
期刊介绍: IJNVO is a forum aimed at providing an authoritative refereed source of information in the field of Networking and Virtual Organisations.
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