Sentiment Analysis of E-commerce Product Reviews Based on BiLSTM Model

被引：0
作者：
Ao, Xiqin [1 ]
Zhao, Liyang [1 ]
Liu, Xingyu [1 ]
Wu, Tingting [1 ]
机构：
[1] Anhui Xinhua Univ, Hefei, Anhui, Peoples R China
来源：
2024 9TH INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND SIGNAL PROCESSING, ICSP | 2024年
关键词：
Sentiment analysis; BiLSTM model; Natural Language Processing; Deep Learning;
D O I：
10.1109/ICSP62122.2024.10743562
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this study, the BiLSTM model is used to improve the accuracy of sentiment analysis. Firstly, CNN, LSTM and their bidirectional version BiLSTM are introduced, highlighting their advantages in processing text time series. The experimental results of constructing a BiLSTM model and conducting verification show that the model is superior to other models in identifying emotional polarity, and has good generalization and high accuracy. This study can not only provide more accurate analysis for the sentiment analysis of e-commerce reviews, but also show the application of deep learning in natural language processing.
引用
收藏
页码：1763 / 1766
页数：4
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