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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 12
3583-3587,3596

Sentiment classification depth model based on word2vec and bi-directional LSTM

Huang Xianying1
Liu Guangfeng1
Liu Xiaoyang1,2
Yang Anzhi1
1. College of Computer Science & Engineering, Chongqing University of Technology, Chongqing 400054, China
2. College of Engineering, University of Alabama, Tuscaloosa Alabama 35401, USA
DOI: 10.19734/j.issn.1001-3695.2018.08.0599

Abstract

Aiming at the problem of prior knowledge and lack of semantic understanding in the traditional sentiment classification model of social network text, this paper proposed a sentiment classification model called WEEF-BILSTM based on word2vec and bi-directional long short-term memory recurrent neural network. It used the CBOW-based word2vec model for corpus to train word vectors, reduced the sparsity between word vectors, and obtained more complete text context information through the bi-directional LSTM neural network to extract the depth word vector features, and then used one-versus-one SVM to classifiy emotions. The experimental results show that the proposed WEEF-BILSTM model has better classification results than other models, and can achieve better accuracy and F value.

Foundation Support

重庆理工大学研究生创新项目(ycx2018245)
重庆市教育委员会人文社会科学研究项目(17SKG144)
国家教育部人文社科青年基金资助项目(16YJC860010)
国家社科基金资助项目(17XXW004)
2018年重庆市科委技术创新与应用示范项目(cstc2018jscx-msybX0049)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.08.0599
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 12
Section: Algorithm Research & Explore
Pages: 3583-3587,3596
Serial Number: 1001-3695(2019)12-013-3583-05

Publish History

[2019-12-05] Printed Article

Cite This Article

黄贤英, 刘广峰, 刘小洋, 等. 基于word2vec和双向LSTM的情感分类深度模型 [J]. 计算机应用研究, 2019, 36 (12): 3583-3587,3596. (Huang Xianying, Liu Guangfeng, Liu Xiaoyang, et al. Sentiment classification depth model based on word2vec and bi-directional LSTM [J]. Application Research of Computers, 2019, 36 (12): 3583-3587,3596. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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