基于Neo4j的中医导引学知识图谱构建  

Construction of TCM Daoyin knowledge graph based on Neo4j

作　　者：谢云霏 贾李蓉[1] 代金刚[2] XIE Yunfei;JIA Lirong;DAI Jingang(Institute of Information on Traditional Chinese Medicine,China Academy of Chinese Medical Sciences,Beijing 100700,China;Experimental Research Center of China Academy of Chinese Medical Sciences,Song Jun National Prominent and Senior TCM Experts Studio)

机构地区：[1]中国中医科学院中医药信息研究所,北京100700 [2]中国中医科学院医学实验中心、宋军全国名老中医药专家传承工作室

出　　处：《中国数字医学》2024年第4期33-38,共6页China Digital Medicine

基　　金：中国中医科学院科技创新工程项目(CI2021A05304)。

摘　　要：目的:以中医导引学的特点为基础构建知识图谱,方便用户查询、学习,传播中医养生保健传统文化,提高健康素质。方法:使用BERT-CRF模型辅以人工校对,对导引功法相关文献进行命名实体识别,根据学科特征制定实体之间的关系,并使用Neo4j构建中医导引学知识图谱。结果:纳入相关文献3152篇,构建的知识图谱共包含2262个实体节点,5108条关系数据,7种实体类别属性,7种关系,并可以使用Neo4j的Cypher查询语言进行知识检索。结论:本知识图谱将中医导引学知识进行可视化展示,可用于构建导引知识检索、智能问答、功法推荐等应用程序与网络平台,开发相关人工智能应用设备,应用于计算机、自动化等学科的研究与生产创新中,同时也可用于深入数据挖掘,发现新研究方向。Objective To construct a knowledge graph based on the characteristics of Traditional Chinese Medicine(TCM)Daoyin(Chinese traditional body building exercise),so as to facilitate users to inquire,learn,spread traditional culture of TCM health care,and improve health quality.Methods The BERT-CRF model and manual proofreading were used to identify the named entities in literatures related to Daoyin practices,and the relationships between entities were established based on the disciplinary characteristics,and a knowledge graph of TCM Daoyin was constructed by using Neo4j.Results A total of 3,152 literatures were included.The constructed knowledge graph contains 2,262 entity nodes,5,108 relational data,7 entity category attributes,and 7 types of relationships.The knowledge graph can be retrieved by using the Cypher query language of Neo4j.Conclusion This knowledge graph can visually display the knowledge of TCM Daoyin,which can be used to build application programs and network platforms such as Daoyin knowledge retrieval,intelligent answering Q&A,and exercise recommendations.It can be used for developing relevant AI application and devices and for research and innovation in computer science and automation fields,and can also be used for in-depth data mining to discover new research directions.

关 键 词：中医药 Neo4j 导引 知识图谱 

分 类 号：R319[医药卫生—基础医学]