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基于中成药知识图谱的知识推理及智能推荐

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目的/意义 构建中成药说明书知识图谱,实现基于知识推理的智能推荐.方法/过程 基于Py2neo结合Neo4j图数据库搭建知识图谱的技术,整理 1 380 种中成药信息并构建数据库,基于三元闭包算法实现知识推理,运用概率模型计算中成药推荐评分.结果/结论 共形成实体概念 11 103 个,语义关系24 种.构建了中成药智能推荐知识图谱,搭建中成药智能推荐平台实现中成药的准确推荐.实现中成药与知识图谱领域结合,为中医辅助诊疗提供方法借鉴,为进一步开展中成药知识可视化研究提供参考.
Knowledge Reasoning and Intelligent Recommendation Based on Knowledge Graph of Chinese Patent Medicine
Purpose/Significance To construct the knowledge graph of Chinese patent medicine instructions,and to realize intelli-gent recommendation based on knowledge reasoning.Method/Process Based on the technology of Py2neo combined with Neo4j graph da-tabase to build knowledge graph,the information of 1 380 kinds of Chinese patent medicine are sorted out and the database is built.Knowledge reasoning is realized based on the triadic closure algorithm,and the recommendation score of Chinese patent medicine is cal-culated by the probability model.Result/Conclusion In the study,11 103 entity concepts and 24 semantic relationships are formed.The knowledge graph of intelligent recommendation of Chinese patent medicine is constructed,and the intelligent recommendation platform of Chinese patent medicine is built to realize accurate recommendation of Chinese patent medicine.The combination of Chinese patent medi-cine and knowledge graph is realized,which provides a method reference for traditional Chinese medicine(TCM)auxiliary diagnosis and treatment,and provides references for further research on knowledge visualization of Chinese patent medicine.

Chinese patent medicineknowledge graphdatabaseknowledge reasoningintelligent recommendation

马宸睿、孟子琪、边新宇、李玥函、赵汉青

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河北大学中医学院 保定 071000

中成药 知识图谱 数据库 知识推理 智能推荐

国家自然科学基金项目河北省教育厅科学研究项目河北省中医药类科研计划项目

82004503BJK20241082021176

2024

医学信息学杂志
中国医学科学院

医学信息学杂志

CSTPCD
影响因子:1.348
ISSN:1673-6036
年,卷(期):2024.45(4)
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