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QAM: Question Answering System Based on Knowledge Graph in the Military

Authors :
Zhong Hongyue
Jike Ge
Dai Xueling
Dong Chen
Jun Peng
Source :
IEEE ICCI*CC
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

To automatically collect information from the Internet and provide it to users for query, much of the existing search engines have been focused on massive and sprawling information. However, we note that the search engines produce a host of answers to specific questions with little accuracy or intelligence. Therefore, we consider the approach of question answering (QA) systems based on the knowledge graph (KG). Resent works are widely shared that the KG can be deeper for the field of medicine and finance, etc. Nowadays, QA system in the military is sorely needed with the dramatic growth of the technology. In this paper, we propose a QA system based on the KG in the military (QAM). Which applies semantic Web technology, and allows a deep analysis of military questions and documents at both representation and interrogation levels. The experimental results reveal that KG applied in the military domain, can make up the inadequacy of the general search engine, return to refine and accurate results, and provide conveniently knowledge service in the military field.

Details

Database :
OpenAIRE
Journal :
2020 IEEE 19th International Conference on Cognitive Informatics & Cognitive Computing (ICCI*CC)
Accession number :
edsair.doi...........0934b9f46548788f4f3acdb278a3d784