一种基于联合深度学习模型的情感分类方法

被引:5
作者
杨艳
徐冰
杨沐昀
赵晶晶
机构
[1] 哈尔滨工业大学计算机科学与技术学院机器智能与翻译实验室
关键词
情感分类; 长短期记忆模型; 卷积神经网络;
D O I
暂无
中图分类号
TP391.1 [文字信息处理];
学科分类号
081203 ; 0835 ;
摘要
针对情感分类问题中长句和短句具有不同的建模特点,提出了一种基于联合深度学习模型的情感分类方法。该方法融合长短期记忆(long-short term memory,LSTM)模型与卷积神经网络(convolutional neural network,CNN)对影视评论数据进行情感极性判别;采用LSTM对上下文进行建模,通过逐词迭代得到上下文的特征向量;采用CNN模型从词向量序列中自动发现特征,抽取局部特征并整合成全局特征来提高分类效果。所提出的方法在COAE2016评测的任务2的情感极性分类任务中,取得最高的系统准确率。
引用
收藏
页码:19 / 25
页数:7
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