Research on text classification model based on ERNIE2.0-DICNN

Youjian Gu; Xingxing Yao; Siyin Luo

doi:10.1117/12.2659644

22 November 2022 Research on text classification model based on ERNIE2.0-DICNN

Youjian Gu, Xingxing Yao, Siyin Luo

Proceedings Volume 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022); 1247518 (2022) https://doi.org/10.1117/12.2659644
Event: Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 2022, Hulun Buir, China

Abstract

In various text classification tasks, models based on bidirectional encoder representations from transformers (BERT) have been widely used, but they may lack the semantic knowledge of phrases and the grammar knowledge of the text. In this paper, we propose a joint model (ERNIE2.0-DICNN) based on enhanced representation through knowledge integration (ERNIE2.0) and deep isometric convolutional neural networks (DICNN). Experiments on THUCNews, Weibo, and IMDB datasets demonstrate the higher accuracy of the proposed method.

Citation Download Citation

Youjian Gu, Xingxing Yao, and Siyin Luo "Research on text classification model based on ERNIE2.0-DICNN", Proc. SPIE 12475, Second International Conference on Advanced Algorithms and Signal Image Processing (AASIP 2022), 1247518 (22 November 2022); https://doi.org/10.1117/12.2659644

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