Document Type
Article
Rights
Available under a Creative Commons Attribution Non-Commercial Share Alike 4.0 International Licence
Disciplines
3. MEDICAL AND HEALTH SCIENCES
Abstract
To meet the high-efficiency question answering needs of existing patients and doctors, this system integrates medical professional knowledge, knowledge graphs, and question answering systems that conduct man-machine dialogue through natural language. This system locates the medical field, uses crawler technology to use vertical medical websites as data sources, and uses diseases as the core entity to construct a knowledge graph containing 44,000 knowledge entities of 7 types and 300,000 entities of 11 kinds. It is stored in the Neo4j graph database, using rule-based matching methods and string-matching algorithms to construct a domain lexicon to classify and query questions. This system has specific practical value in the medical field knowledge graph and question answering system.
DOI
https://doi.org/10.1109/ACCESS.2021.3055371
Recommended Citation
Jiang, Z., Chi, C. & Zhan, Y. (2021). Research on Medical Question Answering System Based on Knowledge Graph. IEEE Access PP vol. 99, pg. 21094 - 21101. doi:10.1109/ACCESS.2021.3055371
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-Share Alike 4.0 International License.