Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 6
1780-1784

Multi-channel closed-loop BiLSTM with anti-degradation strategy for text classification

Sun Zhongyu
Gong Hongfang
Di Junke
School of Mathematics & Statistics, Changsha University of Science & Technology, Changsha 410114, China
DOI: 10.19734/j.issn.1001-3695.2020.06.0161

Abstract

Bidirectional long short-term memory(BiLSTM) and its variants can handle variable length sequences. Due to the complex semantic information of text and the high dimension of embedded text data, BiLSTM shows a weak ability of low-level network learning. And the problem of network degradation is easy to occur when learning high-level feature representation using overlay network layer. In order to solve these problems, this paper proposed a closed-loop BiLSTM module to enrich the semantic representation of hidden state in each layer of network structure. Meanwhile, it used residual connection and enhanced sparse representation strategy to optimize the module, and sparsed the feature vectors of hidden state to alleviate network degradation. Finally, this paper adopted the weighted fusion of multi-channel word embedding and realized the fusion of semantic information and emotional information under the low-dimensional tensor to enrich the text representation of the input layer. This paper verified the datasets of emotional classification and problem classification by experiments. The results show that the proposed model has excellent performance, good classification accuracy and robustness in capturing the expression of text's emotion information.

Foundation Support

国家自然科学基金资助项目(61972055)
湖南省教育厅重点项目(18A145)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2020.06.0161
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 6
Section: Algorithm Research & Explore
Pages: 1780-1784
Serial Number: 1001-3695(2021)06-033-1780-05

Publish History

[2021-06-05] Printed Article

Cite This Article

孙中宇, 龚红仿, 狄俊珂. 基于防退化策略的多通道闭环BiLSTM在文本分类中的应用研究 [J]. 计算机应用研究, 2021, 38 (6): 1780-1784. (Sun Zhongyu, Gong Hongfang, Di Junke. Multi-channel closed-loop BiLSTM with anti-degradation strategy for text classification [J]. Application Research of Computers, 2021, 38 (6): 1780-1784. )

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  • 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.

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