Knowledge modeling and acquisition of traditional Chinese herbal drugs and formulae from text

被引：39
|
作者：
Cao, CG [1 ]
Wang, HT [1 ]
Sui, YF [1 ]
机构：
[1] Chinese Acad Sci, Knowledge Acquisit & Sharing Grp, Key Lab Intelligent Informat Proc, Inst Comp Technol, Beijing 100080, Peoples R China
来源：
ARTIFICIAL INTELLIGENCE IN MEDICINE | 2004年 / 32卷 / 01期
关键词：
traditional Chinese drug; traditional Chinese formula; ontology; knowledge acquisition;
D O I：
10.1016/j.artmed.2004.01.015
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Traditional Chinese medicine has developed over more than 4000 years. A tremendous amount of medical knowledge has been accumulated, among which herbal drugs and formulae are an important portion. This paper presents an ontology for traditional Chinese drugs and formulae, and an ontology-based system for extracting knowledge of drugs and formulae from semi-structured text. The system consists of two components: an executable knowledge extraction Language (or EKEL) for specifying knowledge-extracting agents, and a support machine for executing EKEL programs. Experiments show that the system is adequate of extracting knowledge of herbal drugs and formulae from semi-structured text. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码：3 / 13
页数：11
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