中圖分類(lèi)號(hào)：TP391.1
文獻(xiàn)標(biāo)志碼：A
DOI: 10.16157/j.issn.0258-7998.223108
中文引用格式： 李蕓，潘雅麗，肖冬. 基于改進(jìn)BERT-BiGRU模型的文本情感分類(lèi)研究[J]. 電子技術(shù)應(yīng)用，2023，49(2)：9-14.
英文引用格式： Li Yun，Pan Yali，Xiao Dong. Research on text emotion classification based on improved BERT-BiGRU model[J]. Application of Electronic Technique，2023，49(2)：9-14.

Research on text emotion classification based on improved BERT-BiGRU model

Abstract： Aiming at the problem that the accuracy of text emotion classification of online comment is not high, an improved model based on BERT and bidirectional gated recurrent unit (BiGRU) is proposed. The word vector representation is carried out by using the BERT model which can represent the rich semantic features of the text. The classification effect of the model is improved by combining the BiGRU neural network which can retain the text context related information for a long time. On this basis, the attention mechanism is introduced, to highlight the weight of emotional words which can better express the classification results in the text, and improve the accuracy of emotional classification. The above model was tested on Acllmdb_v1 data set and hotel reviews data set, which are public data set. The experimental results show that the model achieves good performance in both Chinese and English text emotion classification tasks.

Key words : text emotion classification；BERT；BiGRU；attention mechanism