Article Gold Open Access 2022

Analysis of the Reform Effectiveness of Vocational Skill Identification Based on the New Social Training Model in the New Era under Deep Learning Assessment

WY
Wang, Yeming
 RY
Ran, Yong
Applied Bionics and Biomechanics
Journal · Vol. 2022 · Art. 1676355
Abstract

In order to be able to make full use of domain knowledge to improve the performance of skill word extraction, this paper proposes a skill word extraction method based on a combination of deep learning and corpus features. Skill word extraction is transformed into a sequence annotation problem, and based on the basic model of sequence annotation, Bi-LSTM-CRF, corpus features are added to the input layer, and the output of the input layer is connected with the Bi-LSTM output as the input of the CRF layer. The experimental results show timely updating of the question bank, paying attention to the quality of vocational skill identification, and strictly managing the issuance of vocational qualification false certificates. © 2022 Yeming Wang and Yong Ran.

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Index Keywords

Skill human Article vocation Performance Deep learning Long short-term memory Training model Learning assessment attention extraction extraction method Domain Knowledge Input layers Question banks Vocational qualifications
Author Affiliations
Graduate School, Anyang University, Anyang, Gyeonggi-do, South Korea
School of Intelligent Manufacturing, Chongqing Three Gorges Vocational College, Chongqing, Chongqing, China
Funding & Acknowledgements
No funding information
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