情报科学 ›› 2025, Vol. 43 ›› Issue (7): 97-105.

• 理论研究 • 上一篇    下一篇

《金匮要略》中知识元识别与知识描述模型研究

  

  • 出版日期:2025-07-05 发布日期:2025-10-16

  • Online:2025-07-05 Published:2025-10-16

摘要:

【目的/意义】基于知识元理论对《金匮要略》中的中医辨证诊疗知识进行识别与描述,为中医古籍知识描述
与知识组织提供新的方法和路径。【方法/过程】本文首先从知识元理论的视角出发,将知识元理论与《金匮要略》中
的中医辨证知识特点相结合,对《金匮要略》中的知识元和知识单元进行了界定。然后,通过深入到细粒度的知识
层面对知识元进行识别,构建出知识元描述模型与知识单元描述模型,并以书中原文为例进行实例构建。【结果/结
论】本文以中医辨证逻辑链条为粒度,充分利用《金匮要略》文本叙述特点,深度挖掘了其中的中医辨证知识,并利
用知识描述模型,展示了模型在中医古籍知识组织中的可用性和有效性,为细粒度的知识描述与组织提供了新的
视角。【创新/局限】提供了一种从中医古籍文字叙述特点切入,对知识元、知识单元进行层级划分,并基于此将知识
结构进行描述的结构化表示方法。然而,模型的泛化能力需通过大量实践进一步验证。

Abstract:

【Purpose/significance】Based on the knowledge element theory, this study identifies and describes the knowledge of tradi⁃
tional Chinese medicine diagnosis and treatment in the Synopsis of the Golden Chamber, providing a new method and path for the de⁃
scription and organization of knowledge in ancient Chinese medicine books.【Method/process】This study integrates knowledge ele⁃
ment theory with the characteristics of traditional Chinese medicine syndrome differentiation knowledge in Synopsis of the Golden
Chamber to define its knowledge elements and units. We then construct knowledge element and unit description models by examining
the fine-grained knowledge layer, and demonstrate their utility with an example from the original text.【Result/conclusion】This study,
focusing on the granularity of the logic chain of traditional Chinese medicine (TCM) pattern identification, leverages the textual charac⁃
teristics of the Essential Prescriptions from the Synopsis of the Golden Chamber to deeply mine TCM pattern identification knowledge.
By employing a knowledge description model, the study demonstrates the model's applicability and effectiveness in organizing knowl⁃
edge from ancient TCM texts, providing a novel perspective for fine-grained knowledge description and organization.【Innovation/limi⁃
tation】This article provides a structured representation method that starts from the narrative characteristics of ancient Chinese medi⁃
cine texts, divides knowledge elements and knowledge units into hierarchical levels, and describes the knowledge structure based on
this. However, the generalization ability of the model needs to be further validated through extensive practice.