Computer Engineering and Applications ›› 2020, Vol. 56 ›› Issue (24): 157-163.DOI: 10.3778/j.issn.1002-8331.1909-0312

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Text Entailment Recognition Based on Integration of Language Knowledge and Deep Learning

ZHENG Dequan, YU Feng, WANG Hewei   

  1. 1.School of Computer and Information Engineering, Harbin University of Commerce, Harbin 150028, China
    2.School of Computer Science and Technology, Harbin Institute of Technology, Harbin 150001, China
  • Online:2020-12-15 Published:2020-12-15



  1. 1.哈尔滨商业大学 计算机与信息工程学院,哈尔滨 150028
    2.哈尔滨工业大学 计算机科学与技术学院,哈尔滨 150001


Text entailment technology has been widely used in natural language processing, but there are some problems such as the poor reasoning ability of word pairs (for example, there is the antonym pairs in sentence pairs, but can’t judge the antonym relationship, etc.). This paper focuses on the acquisition of knowledge vector from words, including acquire the word pairs relation vector by integration of multi feature and supervised method, acquire word pairs relation expression using TransR tools, and acquire antonym vector expression. Knowledge vector is introduced into the part of word alignment and attention mechanism in text entailment recognition model. The experimental results show that the proposed method is better than the classical model.

Key words: text entailment, knowledge representation, deep learning, word alignment, attention mechanism



关键词: 文本蕴含, 知识向量, 深度学习, 词对齐, 注意力机制