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文章基本信息

  • 标题:Research Progress of Automatic Question Answering System Based on Deep Learning
  • 本地全文:下载
  • 作者:Shiyao Zhao ; Zhezhi Jin
  • 期刊名称:Open Access Library Journal
  • 印刷版ISSN:2333-9705
  • 电子版ISSN:2333-9721
  • 出版年度:2020
  • 卷号:7
  • 期号:6
  • 页码:1-6
  • DOI:10.4236/oalib.1106046
  • 语种:English
  • 出版社:Scientific Research Pub
  • 摘要:With the rapid development of deep learning, a large number of machine reading comprehension models based on deep learning have emerged. Firstly, the paper points out the shortcomings of traditional search engines and explains the advantages of automatic question answering systems compared with them. Secondly, it summarizes the development process of the deep learning-based machine reading comprehension model, and expounds the overall framework and operation principle of the model, as well as the advantages and application scope of the model. Finally, it points out where the development trend lies, and lays the foundation for follow-up researchers.
  • 关键词:Natural Language ProcessingDeep LearningMachine Reading ComprehensionAutomatic Question AnsweringAttention Mechanism
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