Intelligent Question Answering System Based on Domain Knowledge Graph
- 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.
Cite this article
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 -