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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 1
93-96,100

Unsupervised text simplification with sequence-to-sequence model

Li Tianyu
Li Yun
Qian Zhenyu
School of Information Engineering, Yangzhou University, Yangzhou Jiangsu 225137, China
DOI: 10.19734/j.issn.1001-3695.2019.11.0611

Abstract

Training text simplification model based on seq2seq requires large-scale parallel corpora. However, current task lacks large-scale and well-labeled parallel corpora. To address the above issues, this paper proposed an unsupervised text simplification algorithm that made the learning of the model only need simple and complex sentence datasets without labels. First, the method used denoising autoencoder to learn from simple sentence corpus and complex sentence corpus, respectively, to obtain a simple sentence autoencoder and a complex sentence autoencoder. Then, it combined the two autoencoders to form an initial text simplification model and a text complication model. Finally, it used back-translation to convert the unsupervised text simplification problem into a supervised problem, and iteratively optimized the text simplification model. Experiments on the standard dataset show that the method is superior to the existing unsupervised model on the general indicators BLEU and SARI, and the model has simplified effects at both the lexical and syntactic level.

Foundation Support

国家自然科学基金资助项目(61703362)
江苏省研究生科研与实践创新计划项目(SJCX19_0888)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.11.0611
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 1
Section: Algorithm Research & Explore
Pages: 93-96,100
Serial Number: 1001-3695(2021)01-018-0093-04

Publish History

[2021-01-05] Printed Article

Cite This Article

李天宇, 李云, 钱镇宇. 基于序列到序列模型的无监督文本简化方法 [J]. 计算机应用研究, 2021, 38 (1): 93-96,100. (Li Tianyu, Li Yun, Qian Zhenyu. Unsupervised text simplification with sequence-to-sequence model [J]. Application Research of Computers, 2021, 38 (1): 93-96,100. )

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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