Algorithm Research & Explore
|
1033-1037

Dual-channel word vectors based ACRNN for text classification

Xing Xin
Sun Guozi
School of Computer Science, Nanjing University of Posts & Telecommunications, Nanjing 210023, China

Abstract

Common models of text classification are mostly constructed with recurrent neural network and convolutio-nal neural network in a stacked way. Although this stacked structure can extract more high-dimensional and deeper semantic information, a part of the effective feature information is also dropped when different structures are connected. In order to solve the above problem, this paper proposed a classification model based on dual-channel word vectors, and the model used a shallower structure with attention-mechanism-based Bi-LSTM and CNN to extract features of text representation effectively. In addition, this paper presented a new method to characterize text into two forms, forward and backward, and used CNN to extract feature information of the text. By conducting classification experiments on two different five-classification datasets and comparing with a variety of benchmark models, it verifies that the model is effective and the results show that this model is superior to the other models with stacked structure.

Foundation Support

国家自然科学基金资助项目(61502247)
数学工程与先进计算国家重点实验室开放基金资助项目(2017A10)
信息网络安全公安部重点实验室开放课题基金资助项目(C17611)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.05.0127
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 4
Section: Algorithm Research & Explore
Pages: 1033-1037
Serial Number: 1001-3695(2021)04-013-1033-05

Publish History

[2021-04-05] Printed Article

Cite This Article

邢鑫, 孙国梓. 基于双通道词向量的ACRNN文本分类 [J]. 计算机应用研究, 2021, 38 (4): 1033-1037. (Xing Xin, Sun Guozi. Dual-channel word vectors based ACRNN for text classification [J]. Application Research of Computers, 2021, 38 (4): 1033-1037. )

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.


Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)