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

Authors: Jun Chen

Addresses: School of Continuing Education, Changzhou Vocational Institute of Mechatronic Technology, Changzhou, 213164, China

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.

Keywords: Apriori algorithm; data mining; teaching evaluation; mobile platform; elderly education; association rules.

DOI: 10.1504/IJNVO.2023.133877

International Journal of Networking and Virtual Organisations, 2023 Vol.28 No.2/3/4, pp.348 - 363

Received: 22 Dec 2022
Accepted: 04 May 2023
Published online: 04 Oct 2023 *

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