[1]魏苏波,张顺香,朱广丽,等.基于正交投影的BiLSTM-CNN情感特征抽取方法[J].南京师大学报(自然科学版),2023,46(01):139-148.[doi:10.3969/j.issn.1001-4616.2023.01.018]
　Wei Subo,Zhang Shunxiang,Zhu Guangli,et al.An Emotion Feature Extraction Method of BiLSTM-CNN based on Orthogonal Projection[J].Journal of Nanjing Normal University(Natural Science Edition),2023,46(01):139-148.[doi:10.3969/j.issn.1001-4616.2023.01.018]
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基于正交投影的BiLSTM-CNN情感特征抽取方法()
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《南京师大学报（自然科学版）》[ISSN:1001-4616/CN:32-1239/N]

卷:
第46卷
期数:
2023年01期
页码:
139-148
栏目:
计算机科学与技术
出版日期:
2023-03-15

文章信息/Info

Title:
An Emotion Feature Extraction Method of BiLSTM-CNN based on Orthogonal Projection
文章编号:
1001-4616(2023)01-0139-10
作者:
魏苏波1; 2; 张顺香1; 2; 朱广丽1; 2; 孙争艳1; 2; 李 健1; 2
(1.安徽理工大学计算机科学与工程学院，安徽 淮南 232001)
(2.合肥综合性国家科学中心人工智能研究院，安徽 合肥 230000)
Author(s):
Wei Subo1; 2; Zhang Shunxiang1; 2; Zhu Guangli1; 2; Sun Zhengyan1; 2; Li Jian1; 2
(1.School of Computer Science and Engineering, Anhui University of Science and Technology, Huainan 232001, China)
(2.Artificial Intelligence Research Institute of Hefei Comprehensive National Science Center, Hefei 230000, China)
关键词:
文本情感分类; 正交投影; BiLSTM; CNN
Keywords:
emotional classification;  orthogonal projection;  BiLSTM;  CNN
分类号:
TP391.1
DOI:
10.3969/j.issn.1001-4616.2023.01.018
文献标志码:
A
摘要:
基于正交投影的BiLSTM-CNN的情感特征抽取方法旨在从文本中获取带权重的中性词向量,得到具有更高区分度的情感特征,为文本情感分类提供有力的技术支持. 传统的深度学习模型会忽略关键局部上下文信息中的特殊意义词,导致获取的情感特征不够丰富. 针对这一问题,本文提出一种基于正交投影的BiLSTM-CNN情感特征抽取方法. 首先,将中性词向量投影到情感极性词的正交空间中,得到加权中性词向量,同时通过CNN深度学习模型抽取文本关键语义; 然后,利用BiLSTM-Attention模型和带权重的中性词向量,从提取出的关键语义中学习可增强句子情感的语义特征,使文本在情感分类时更具判别性. 实验结果表明本文所提出的情感特征抽取方法可以获取更完整的情感特征,从而显著提高文本情感分类的准确率.
Abstract:
The emotion feature extraction method of BiLSTM-CNN based on orthogonal projection aims to obtain the weighted neutral word vector from the text,obtain the emotion feature with higher discrimination,and provide strong technical support for text emotion classification. The traditional deep learning model ignores the special meaning of words in the key local context information,resulting in the insufficient acquisition of emotional features. To solve this problem,a BiLSTM-CNN emotion feature extraction method based on orthogonal projection has been proposed. Firstly,the neutral word vector is projected into the orthogonal space of emotional polarity words,and the weighted neutral word vector is obtained. At the same time,the CNN deep learning model is used to extract the key semantics of the text. Then,the BiLSTM-Attention model and weighted neutral word vector are used to learn the semantic features of sentence emotion from the extracted key semantics,which makes the text more discriminative in sentiment classification. The experimental results show that the proposed sentiment feature extraction method can obtain more complete sentiment features,thus significantly improving the accuracy of text sentiment classification.

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备注/Memo

备注/Memo:
收稿日期:2022-08-08.
基金项目:国家自然科学基金面上项目(62076006)、安徽高校协同创新项目(GXXT-2021-008)、安徽省重点研发计划国际科技合作专项(202004b11020029)、安徽理工大学研究生创新基金项目(2021CX2110).
通讯作者:张顺香,博士,教授,博士生导师,研究方向:语义搜索、情感计算. E-mail:sxzhang@aust.edu.cn
更新日期/Last Update: 2023-03-15