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

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.