现代信息科技2024，Vol.8Issue(4)：101-105,5.DOI:10.19850/j.cnki.2096-4706.2024.04.021
基于集成算法的在线购物平台消费者评价情感分析与研究
Sentiment Analysis and Research on Consumer Evaluation of Online Shopping Platform Based on Integrated Algorithm
袁钰喜 1陈义安 2刘晓慧1
作者信息
- 1. 重庆工商大学 数学与统计学院,重庆 400067
- 2. 重庆工商大学 数学与统计学院,重庆 400067||经济社会应用统计重庆市重点实验室,重庆 400067
- 折叠
摘要
Abstract
This paper performs sentiment analysis and classification on consumer evaluation data from online shopping platforms.By using Python to realize automatic browser driving and anti-crawler technology,it successfully collects consumer evaluation information of a certain shopping platform.This paper proposes an improved integration algorithm,which uses LSTM,BiGRU and BiLSTM as classifiers,and uses Voting and Bagging methods for integration respectively.The results show that compared with the traditional Bayesian and logistic regression,the LSTM+Bagging integration algorithm improves the accuracy by 5.9％and 6％,respectively,and compared with the LSTM+Voting integration algorithm,the accuracy increases by 0.5 percentage points.In addition,the LSTM+Bagging model outperforms the LSTM+Voting algorithm in terms of stability and robustness.关键词
LSTM模型/Voting/Bagging/电商购物Key words
LSTM model/Voting/Bagging/E-Commerce shopping分类
信息技术与安全科学引用本文复制引用
袁钰喜,陈义安,刘晓慧..基于集成算法的在线购物平台消费者评价情感分析与研究[J].现代信息科技,2024,8(4):101-105,5.
