计算机与数字工程Issue(9)：2227-2232,6.DOI:10.3969/j.issn.1672-9722.2019.09.024
基于BLSTM和注意力机制的电商评论情感分类模型∗
Sentiment Classification Model Based on BLSTM and Attentional Mechanism
摘要
Abstract
With the rapid development of the Internet,the sentiments contained in ecommerce reviews is increasingly impor?tant to businesses. In the face of massive data,traditional methods of sentiment classification based on sentiment dictionaries and machine learning methods are no longer suitable for use. In order to effectively learn the text features and reduce the impact of redun?dant noise during the sentiment classification,a sentiment classification model based on bi-directional short and long-term memory network(BLSTM)and attentional mechanism is proposed. The experiment results show that compared with the traditional machine learning methods and ordinary deep learning methods,the model in the precison,recall rate and F1 score have significantly im?proved.关键词
电商评论/情感分类/双向长短时记忆网络/注意力机制Key words
ecommerce reviews/sentiment classification/bi-directional short and long-term memory network(blstm)/at⁃tentional mechanism分类
数理科学引用本文复制引用
潘晓英,赵普,赵倩..基于BLSTM和注意力机制的电商评论情感分类模型∗[J].计算机与数字工程,2019,(9):2227-2232,6.基金项目
国家自然科学基金(编号:61105064) （编号:61105064）
陕西省教育厅专项科研计划项目(编号:14JK1667) （编号:14JK1667）
西安邮电大学创新基金(编号:103-60208007)资助. （编号:103-60208007）
