Research on the English Text Comprehension Model for Higher Vocational Colleges Based on BER
Year: 2025
Type: conference-paper
Abstract: This study explores the BERT-based higher vocational English text comprehension model in the hope of improving the text classification and semantic comprehension ability in higher vocational English teaching. Relevant experiments were carried out with the help of the higher vocational English dataset released in 2024, creating a multi-category English vocabulary classification pattern. The final results of the experiment confirmed that the BERT-based model is superior to other machine learning models in terms of accuracy, reasoning time and resource usage, especially when dealing with complex language structures and semantic information conditions. The application of the BERT model provides an effective strategy for intelligent assistance in higher vocational English teaching.
Author: Ting Hu
Institution: Guangzhou Huashang Vocational College
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: hybrid
OpenAlex ID: W4414386113