Research on Template-Based Factual Automatic Question Answering Technology

  • Wenhui Hu
  • Xueyang LiuEmail author
  • Chengli Xing
  • Minghui Zhang
  • Sen Ma
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11910)


With the increase of people’s demand for information retrieval, question answering system as a new generation of retrieval methods has attracted more and more attention. This paper proposes an automated template generation method based on remote supervision. In the process of generating template, in order to identify the keywords express the semantics of the problem, this paper designs an algorithm to mapping entity relationship to keywords by using pattern mining and statistical methods. This method implements automation of template generation, and makes the templates more accurate. For the template matching, by Deep-learning-based template matching algorithm, this paper use vector to represent words, and designs a tree-based convolutional neural network to extract features of the dependency syntax information. Building a neural network model for template prediction. Experimental results show that the above method can effectively improve the matching accuracy compared with the traditional template matching method.


Question answering system Knowledge graph Template generation Template matching Neural network 



Supported by the 2018 project Research and Application of Key Technologies on Online Monitoring, Efficient Operation and Maintenance and Intelligent Evaluation of Health Condition of Electrical Equipment’ in state Power Grid Corporation (No. PDB17201800280), and Major State Research Development Program of China (No. 2016QY04W0804).


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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Wenhui Hu
    • 1
  • Xueyang Liu
    • 1
    Email author
  • Chengli Xing
    • 2
  • Minghui Zhang
    • 3
  • Sen Ma
    • 1
  1. 1.National Engineering Research Center for Software EngineeringPeking UniversityBeijingChina
  2. 2.SiChuan Tianfu Bank Co., Ltd.NanchongChina
  3. 3.Handan Institute of InnovationPeking UniversityHandan, BeijingChina

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