Title: The method of interest text recommendation in English education based on data mining

Authors: Linlin Fan

Addresses: Department of Tourism Management, Henan Vocational College of Agriculture, Zhengzhou 451450, China

Abstract: In order to solve the problems of low accuracy and lengthy time consumption of traditional English educational interest recommendation methods, a text recommendation method based on data mining is proposed in this paper. An English education text classification system is built, and according to the classification results, user interest areas are determined, based on the setting behaviour data in the information domain. Clear targets are recommended, users' English browsing data are obtained and standardised, a user interest degree apriori algorithm combined with data association rules is established, and finally the complete English educational text recommendation using an association rule mining algorithm is presented. The experiment results show that the proposed method has a high precision of recommendation, and the precision and recall rate are significantly better than those of the traditional methods. Hence, effective theoretical support for the research in related fields is provided.

Keywords: data mining; English education; text recommendation; interest text; association rules.

DOI: 10.1504/IJCEELL.2022.124031

International Journal of Continuing Engineering Education and Life-Long Learning, 2022 Vol.32 No.3, pp.374 - 388

Received: 21 Feb 2020
Accepted: 03 Aug 2020
Published online: 11 Jul 2022 *

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