| 引用本文: |
任高,张伦伦,李冉,刘青萍,邹北骥.中医不寐知识图谱构建与知识发现[J].湖南中医药大学学报,2023,43(9):1664-1671[点击复制] |
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| 中医不寐知识图谱构建与知识发现 |
| 任高,张伦伦,李冉,刘青萍,邹北骥 |
| (湖南中医药大学信息科学与工程学院, 湖南 长沙 410208;中南大学计算机学院, 湖南 长沙 410083) |
| 摘要: |
| 目的 系统梳理中医不寐知识，构建中医不寐知识图谱，实现知识关联、知识融合及深度挖掘，为智能化诊疗提供新的路径与方法。方法 以《景岳全书》《类证治裁》等中医古籍和《中医内科学》《针灸学》等国家规划教材为数据来源，通过本体构建、语义消歧等方法得到结构化数据，利用Cypher语言导入Neo4j数据库，构建中医不寐知识图谱，并进行知识检索和知识发现。结果 构建出包含527个节点、1 067条关系的中医不寐知识图谱，并从理、法、方、药4个方面入手，完成了知识检索与知识发现。结论 中医不寐知识图谱可以使用户直观、高效地获取相关知识，了解改善睡眠的方法，有效助推传统医学的继承与发展，为中医智能辅助诊疗提供新思路。 |
| 关键词: 不寐 知识图谱 本体构建 Protégé软件 Neo4j图数据库 知识发现 |
| DOI：10.3969/j.issn.1674-070X.2023.09.017 |
| 投稿时间：2023-06-13 |
| 基金项目:国家重大科技专项项目（2018AAA0102100）；湖南省教育厅科学研究优秀青年项目（22B0385）；2022年度学科建设“揭榜挂帅”项目（22JBZ051）；湖南中医药大学中医学国内一流建设学科开放基金（2018ZYX17）；湖南省中医药管理局智慧中医工程技术重点研究室。 |
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| Knowledge graph construction and knowledge discovery of insomnia in TCM |
| REN Gao,ZHANG Lunlun,LI Ran,LIU Qingping,ZOU Beiji |
| (School of Informatics, Hunan University of Chinese Medicine, Changsha, Hunan 410208, China;School of Computer Science and Engineering, Central South University, Changsha, Hunan 410083, China) |
| Abstract: |
| Objective This paper aims to systematically comb out the knowledge of insomnia in TCM, construct a TCM insomnia knowledge graph, and achieve knowledge association, integration, and in-depth exploration, thereby providing new pathways and methods for intelligent diagnosis and treatment. Methods The data sources for this paper include ancient TCM books such as Jingyue Quanshu and Leizheng Zhicai as well as national planning textbooks such as Internal Medicine of Chinese Medicine and Acupuncture and Moxibustion. Structured data was obtained through ontology construction, semantic disambiguation, and other methods. The Cypher language was used to import Neo4j database to construct the TCM insomnia knowledge graph, and knowledge retrieval and discovery were carried out. Results A TCM insomnia knowledge graph with 527 nodes and 1 067 relationships was constructed, and knowledge retrieval and discovery were carried out from the four aspects of principles, methods, formulas, and medicines. Conclusion The TCM insomnia knowledge graph enables users to access relevant knowledge intuitively and efficiently, and understand the methods for improving sleep, which can effectively contribute to the inheritance and development of traditional medicine and provide new ideas for intelligent-assisted TCM diagnosis and treatment. |
| Key words: insomnia knowledge graph ontology construction Protégé software Neo4j graph database knowledge discovery |
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