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作 者:沈旺[1] 于琳[1] 冯欣[1] 陈晓美[1] 温雯婷 Shen Wang;Yu Lin;Feng Xin;Chen Xiaomei;Wen Wenting(School of Business and Management,Jilin University,Changchun 130012,China;College of Traditional Chinese Medicine·College of Integrated Chinese and Western Medicine,Nanjing University of Chinese Medicine,Nanjing 210023,China)
机构地区:[1]吉林大学商学与管理学院,吉林长春130012 [2]南京中医药大学中医学院·中西医结合学院,江苏南京210023
出 处:《现代情报》2025年第2期26-37,共12页Journal of Modern Information
基 金:国家社会科学基金冷门绝学专项研究项目“本草典籍整理、知识组织与智慧化建设研究”(项目编号:23VJXT024)。
摘 要:[目的/意义]通过构建动态知识图谱实现中医疫病古籍知识动态组织与可视化,并依此挖掘中医疫病古籍隐性知识。[方法/过程]构建融合动态元素的中医疫病古籍知识元语义描述模型,以温病学派为例,基于知识元语义描述模型和深度学习技术进行知识抽取并构建动态知识图谱,结合知识计算方法对温病学派疫病古籍知识进行组方用药规律演化分析以及辩证发展规律探析。[结果/结论]结果表明,随着时间推移,温病学派逐渐偏向使用甘苦寒类中药,各时期疫病症状描述较为一致,辩证理论日益扩充,研究揭示了中医疫病古籍知识演化发展规律并为中医古籍知识发现等相关研究提供新思路。[Purpose/Significance]This research realizes the dynamic organization and visualization of ancient literatures of traditional Chinese medicine(TCM)epidemics by constructing dynamic knowledge graph,and mines the hidden knowledge of ancient literatures of TCM epidemics.[Method/Process]The study proposed a knowledge element semantic description model of ancient literatures of TCM epidemics with dynamic elements,and based on this model and deep learning techniques the research took the warm disease school as an example to perform knowledge extraction and construct dynamic knowledge graph,and combined the knowledge computing method to analyze the evolution of the prescription and medication laws of the ancient books of the warm disease school as well as to analyze the laws of discernment and development.[Result/Conclusion]The results show that with the time,the warm disease school gradually prefer using sweet,bitter and cold herbs,the description of epidemic disease symptoms are relatively consistent in each period,and the theories of syndrome differentiation are increasingly expanded.The study reveals the evolutionary development laws of TCM epidemic knowledge and provides new ideas for the discovery of TCM knowledge and other related researches.
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