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Application research of improved Apriori algorithm in teaching evaluation of mobile platform for elderly education

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  • Jun Chen

Abstract

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.

Suggested Citation

  • Jun Chen, 2023. "Application research of improved Apriori algorithm in teaching evaluation of mobile platform for elderly education," International Journal of Networking and Virtual Organisations, Inderscience Enterprises Ltd, vol. 28(2/3/4), pages 348-363.
    • Handle: RePEc:ids:ijnvor:v:28:y:2023:i:2/3/4:p:348-363
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