| 面向文献组织的重大公共卫生事件知识图谱构建研究 |
| 修订日期：2020-12-07 点此下载全文 |
| 引用本文：李晓瑛,蔡妙芝,李军莲,等.面向文献组织的重大公共卫生事件知识图谱构建研究[J].医学信息学杂志,2021,42(3):8-13, 19 |
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| 基金项目:国家社科基金项目“大数据时代的中西医知识组织与知识图谱构建研究”(项目编号:20BTQ062)；中国医学科学院医学信息研究所新冠肺炎疫情专项“面向文献组织的新冠肺炎知识图谱构建研究”(项目编号:2020XG023)；科技创新2030-“新一代人工智能”重大项目课题“中文医学术语体系构建”(项目编号:2019AAA0104901)；新闻出版业科技与标准重点实验室《医学融合出版知识技术实验室》。 |
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| 中文摘要:提出一种融合中西医知识的新型冠状病毒肺炎知识模型及基于自然语言处理的领域知识自动发现方法,从等级体系结构、主题分类、关系类型等多维度对语义知识进行组织与关联。收集新冠肺炎专题文献、诊疗方案及网络新媒体数据,在自动知识发现基础上进行人工审核和标注,构建新冠肺炎知识图谱并实现可视化呈现与在线检索,以期支撑生物医学科技文献资源深度组织和有效利用。 |
| 中文关键词:新型冠状病毒肺炎 知识图谱 知识发现 知识组织 自然语言处理 |
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| Study on the Building of Knowledge Graph of Major Public Health Events for Literature Organization |
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| Abstract:A COVID-19 knowledge model integrating traditional Chinese and western medicine knowledge and an automatic domain knowledge discovery method based on Natural Language Processing (NLP) are proposed, and the semantic knowledge is organized and associated from the hierarchical structure, subject classification, relation types and other dimensions. Additionally, the COVID-19 literature, diagnosis and treatment regimens and the new media data are collected for knowledge discovery and manual annotation, and the COVID-19 knowledge graph is built and realized for visual presentation and online retrieval, so as to support the well organization and effective utilization of biomedical literature resources. |
| keywords:COVID-19 knowledge graph knowledge discovery knowledge organization Natural Language Processing (NLP) |
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