数字中医药（英文）2022，Vol.5Issue(4)：386-393,8.DOI:10.1016/j.dcmed.2022.12.005
基于知识图谱的中医药知识推理研究
Research on knowledge reasoning of TCM based on knowledge graphs
摘要
Abstract
With the widespread use of Internet, the amount of data in the field of traditional Chinese medicine (TCM) is growing exponentially. Consequently, there is much attention on the col-lection of useful knowledge as well as its effective organization and expression. Knowledge graphs have thus emerged, and knowledge reasoning based on this tool has become one of the hot spots of research. This paper first presents a brief introduction to the development of knowledge graphs and knowledge reasoning, and explores the significance of knowledge reasoning. Secondly, the mainstream knowledge reasoning methods, including knowledge reasoning based on traditional rules, knowledge reasoning based on distributed feature rep-resentation, and knowledge reasoning based on neural networks are introduced. Then, using stroke as an example, the knowledge reasoning methods are expounded, the principles and characteristics of commonly used knowledge reasoning methods are summarized, and the re-search and applications of knowledge reasoning techniques in TCM in recent years are sor-ted out. Finally, we summarize the problems faced in the development of knowledge reason-ing in TCM, and put forward the importance of constructing a knowledge reasoning model suitable for the field of TCM.关键词
中医药/脑卒中/知识图谱/知识推理/辅助决策/TransE模型Key words
Traditional Chinese medicine (TCM)/Stroke/Knowledge graph/Knowledge reasoning/Assisted decision-making/Transloction Embedding (TransE)model引用本文复制引用
郭志恒,刘青萍,邹北骥..基于知识图谱的中医药知识推理研究[J].数字中医药（英文）,2022,5(4):386-393,8.基金项目
The National Key R&D Program of China(2018AAA0102100),Hunan Provincial Department of Education Outstanding Youth Project(22B0385),Open Fund of the Domestic First-class Discipline Construction Project of Chinese Medicine of Hunan University of Chinese Medicine(2018ZYX17),Electronic Science and Technology Discipline Open Fund Project of School of In-formation Science and Engineering,Hunan University of Chinese Medicine(2018-2),and Hunan University of Chinese Medicine Graduate Innovation Project(2022CX122). （2018AAA0102100）
