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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 38, 2021 No. 11
3268-3273

Research on span-extraction algorithm for machine reading comprehension

Ye Junmin
Zhao Xiaoli
Du Xiang
Yao Xiantan
School of Computer Science, Central China Normal University, Wuhan 430000, China
DOI: 10.19734/j.issn.1001-3695.2021.04.0106

Abstract

The existing machine reading comprehension models mainly use the recurrent neural network to process the text sequence information, which easily leads to slow down the training and prediction speed, and low accuracy of model prediction, this paper proposed a span-extraction machine reading comprehension algorithm QA-Reader. The algorithm first used a large pre-trained language model RoBERTa-www-ext to obtain the word embedding representations of questions and text. Secondly, it used deep separable convolution neural network and multi-head self-attention mechanism to encode. Then it calculated the bidirectional attention and the text's self-attention to fuse the correlation information between text and problem, and splicing to get the final semantic representation. Finally, the model encoder predicted the answer. For the unanswerable questions, the model calculated the unanswerable probability. Experiments were carried out on the Chinese span-extraction machine reading comprehension datasets. The results show that compared with the baseline model, the QA-Reader model has improved EM and F1 values by 3.821% and 2.740% in performance, and the training speed has improved by 0.089%.

Foundation Support

国家社会科学基金后期资助项目(20FTQB020)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2021.04.0106
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 11
Section: Algorithm Research & Explore
Pages: 3268-3273
Serial Number: 1001-3695(2021)11-011-3268-06

Publish History

[2021-11-05] Printed Article

Cite This Article

叶俊民, 赵晓丽, 杜翔, 等. 片段抽取型机器阅读理解算法研究 [J]. 计算机应用研究, 2021, 38 (11): 3268-3273. (Ye Junmin, Zhao Xiaoli, Du Xiang, et al. Research on span-extraction algorithm for machine reading comprehension [J]. Application Research of Computers, 2021, 38 (11): 3268-3273. )

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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