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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 2
371-375,394

Effective method in sentence compression based on pre-reading and simple attention mechanism

Lu Zhonglei1
Liu Wenfen2
Zhou Yanfang1
Hu Xuexian1
Wang Binyu1
1. State Key Laboratory of Mathematical Engineering & Advanced Computer, Zhengzhou 450001, China
2. Guangxi Key Laboratory of Cryptogpraphy & Information Security, School of Computer Science & Information Security, Guilin University of Electronic Technology, Guilin Guangxi 541004, China
DOI: 10.19734/j.issn.1001-3695.2017.08.0720

Abstract

This paper proposed a method in English sentence compression based on pre-reading and simple attention mechanism. On the basis of GRU and encoder-decoder, this paper modeled the original sentence semantics twice in the encoding stage. It used the first result as a global information to strengthen the second semantic model, thus obtaining a more comprehensive and accurate semantic vector. With full consideration of the particularity of the deleted sentence compression, this paper simply adopted the 3t-attention mechanism in the decoding stage to improve the efficiency and accuracy of prediction, which meant that the semantic vectors most relevant to the current decoding time step were inputted to the decoder. The results from the experiments on the Google news sentence compression dataset show that this model significantly outperforms all the recent state-of-the-art methods. Therefore, pre-reading and simple attention mechanism can effectively improve the accuracy of English sentence compression.

Foundation Support

国家自然科学基金资助项目(61862011,61502527)
广西自然科学基金资助项目(2018GXNSFAA138116)
广西密码学与信息安全重点实验室开放课题项目(GCIS201704)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.08.0720
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Algorithm Research & Explore
Pages: 371-375,394
Serial Number: 1001-3695(2019)02-013-0371-05

Publish History

[2019-02-05] Printed Article

Cite This Article

鹿忠磊, 刘文芬, 周艳芳, 等. 基于预读及简单注意力机制的句子压缩方法 [J]. 计算机应用研究, 2019, 36 (2): 371-375,394. (Lu Zhonglei, Liu Wenfen, Zhou Yanfang, et al. Effective method in sentence compression based on pre-reading and simple attention mechanism [J]. Application Research of Computers, 2019, 36 (2): 371-375,394. )

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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