CNN blend ERNIE for sentiment classification

Yun Peng Xu; Hui Cao

doi:10.1117/12.2681111

23 May 2023 CNN blend ERNIE for sentiment classification

Yun Peng Xu, Hui Cao

Proceedings Volume 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023); 126454D (2023) https://doi.org/10.1117/12.2681111
Event: International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 2023, Hangzhou, China

Abstract

For Chinese text sentiment classification task, this paper propose the CNN blend ERNIE for Sentiment Classification (CSEC) model, it concatenates all CLS vectors from twelve Encode Layers of Enhanced Representation through Knowledge Integration (ERNIE) by introducing Attention Mechanism (AM) then sends the combined vector to Convolutional Neural Networks (CNN). It aims to learn different levels of information from different layers. Through different experiments to validate, CESC achieves the best results.

Citation Download Citation

Yun Peng Xu and Hui Cao "CNN blend ERNIE for sentiment classification", Proc. SPIE 12645, International Conference on Computer, Artificial Intelligence, and Control Engineering (CAICE 2023), 126454D (23 May 2023); https://doi.org/10.1117/12.2681111

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