JOURNAL OF LIGHT INDUSTRY

CN 41-1437/TS  ISSN 2096-1553

Volume 35 Issue 5
October 2020
Article Contents
YAO Ni, GAO Zhengyuan, LOU Kun and et al. Research on sentiment classification for online reviews based on BERT and BiGRU[J]. Journal of Light Industry, 2020, 35(5): 80-86. doi: 10.12187/2020.05.011
Citation: YAO Ni, GAO Zhengyuan, LOU Kun and et al. Research on sentiment classification for online reviews based on BERT and BiGRU[J]. Journal of Light Industry, 2020, 35(5): 80-86. doi: 10.12187/2020.05.011 shu

Research on sentiment classification for online reviews based on BERT and BiGRU

  • Received Date: 2020-07-01
  • Aiming at the problem of inaccurate sentiment classification for online comment texts of Internet users, an online reviews sentiment classification model was proposed based on BERT and BiGRU.The model used the Word2Vec framework to represent the word vector of the text content, then extracted the deep dynamic representation of the word vector by the BERT pre-training model,and finally input it into the BiGRU network for sentiment classification.The experimental results demonstrated that compared with the dual-path LSTM combined with Attention mechanism model (W2V-BiLSTM-Attention), traditional convolutional neural network model (W2V-CNN) and traditional recurrent neural network model (W2V-RNN), the MicroF1 value of this model was the highest (0.91) with the best classification results.
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