Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022)

Medical Knowledge Question Answering System Based on Knowledge Graph

Authors
Junwei Li1, *
1Computer Science and Technology, Gannan University of Science and Technology, Ganzhou, 341000, Jiangxi, China
*Corresponding author. Email: ljw687520@126.com
Corresponding Author
Junwei Li
Available Online 29 December 2022.
DOI
10.2991/978-2-494069-31-2_267How to use a DOI?
Keywords
Knowledge graph; Question answering system; Medical
Abstract

Knowledge graph has broad application prospects in the field of medical question answering. The research first builds Neo4J knowledge graph based on Chinese OpenKG.cn structured medical common sense data, and then builds a question answering system based on the constructed knowledge graph. The steps include constructing a complete and usable graph from data collection, data representation, and implementing a general graph construction tool, and then using a pipelined question answering system model to build a medical commonsense question answering system, and finally look forward to the application prospects and industry development trends of question answering systems in different medical fields.

Copyright
© 2022 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.

Download article (PDF)

Volume Title
Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022)
Series
Advances in Social Science, Education and Humanities Research
Publication Date
29 December 2022
ISBN
10.2991/978-2-494069-31-2_267
ISSN
2352-5398
DOI
10.2991/978-2-494069-31-2_267How to use a DOI?
Copyright
© 2022 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  - Junwei Li
PY  - 2022
DA  - 2022/12/29
TI  - Medical Knowledge Question Answering System Based on Knowledge Graph
BT  - Proceedings of the 2022 6th International Seminar on Education, Management and Social Sciences (ISEMSS 2022)
PB  - Atlantis Press
SP  - 2268
EP  - 2273
SN  - 2352-5398
UR  - https://doi.org/10.2991/978-2-494069-31-2_267
DO  - 10.2991/978-2-494069-31-2_267
ID  - Li2022
ER  -