Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)

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Intelligent Question Answering System Based on Domain Knowledge Graph

Authors
Yiming Hao1, Ye Wu1, *, Luo Chen1, 2, Kaijun Yang3
1College of Electronic Science and Technology, National University of Defense Technology, Changsha, Hunan, China
2Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region, Ministry of Natural Resources, Changsha, Hunan, China
3The Second Surveying and Mapping Institute of Hunan, Changsha, Hunan, China
*Corresponding author. Email: yewugfkd@nudt.edu.cn
Corresponding Author
Ye Wu
Available Online 27 December 2022.
DOI
10.2991/978-94-6463-040-4_21How to use a DOI?
Keywords
Knowledge graph; Intelligent question answering system; Deep learning; Text classification
Absrtact

This paper introduces an intelligent question answering system based on the domain knowledge graph of military battle cases. Through the collection and accumulation of military big data, we first build a domain knowledge graph for military battle cases, and then use natural language processing related technologies to understand natural language problems, mainly intention recognition and slot filling. On problem intent identification. In this paper, BERT + TextCNN model is proposed to realize the intention classification of questions. LAC is used to segment the natural language questions and extract the entities in the question sentence in slot filling. The answer is then retrieved from the knowledge graph. The test results show that the accuracy of question comprehension in the question set is more than 90%, and it can answer most of the questions in the field quickly and accurately.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title
Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
Series
Atlantis Highlights in Computer Sciences
Publication Date
27 December 2022
ISBN
10.2991/978-94-6463-040-4_21
ISSN
2589-4900
DOI
10.2991/978-94-6463-040-4_21How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Yiming Hao
AU  - Ye Wu
AU  - Luo Chen
AU  - Kaijun Yang
PY  - 2022
DA  - 2022/12/27
TI  - Intelligent Question Answering System Based on Domain Knowledge Graph
BT  - Proceedings of the 2022 3rd International Conference on Artificial Intelligence and Education (IC-ICAIE 2022)
PB  - Atlantis Press
SP  - 137
EP  - 142
SN  - 2589-4900
UR  - https://doi.org/10.2991/978-94-6463-040-4_21
DO  - 10.2991/978-94-6463-040-4_21
ID  - Hao2022
ER  -