Title: Research on the method of educational text classification based on deep learning

Authors: Yuqin Wang

Addresses: Department of Basic Course Teaching, Rongzhi College of Chongqing Technology and Business University, Chongqing 401320, China

Abstract: To improve the efficiency of traditional text classification methods of education and the recall rate of research objectives, we propose an educational text classification method based on the depth of learning. The English web pages covering the economics, politics, sports, entertainment, and life, etc., which involve carriers containing explanatory texts and discussion papers, etc., will be used as the source of English educational texts for corresponding collection and processing. We upload the collected texts, introduce deep learning algorithms, perform preprocessing and feature learning, and input the learning features into the deep learning Softmax classifier based on the learning results. The output of the classifier consists of the classification results of the educational texts. Experiment results show that the proposed method of classification gives good accuracy and high recall rate, and the average distribution time is only 3.992 s. Hence, the proposed method can effectively improve the classification efficiency of educational texts.

Keywords: deep learning; educational text; text classification; learning characteristics; English education.

DOI: 10.1504/IJCEELL.2022.124032

International Journal of Continuing Engineering Education and Life-Long Learning, 2022 Vol.32 No.3, pp.313 - 326

Received: 13 Jan 2020
Accepted: 04 Jun 2020
Published online: 11 Jul 2022 *

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