摘要
该文分析了痛风临床诊治智能教学系统(IntelligentTutoringSystemfortheInstructionofGoutClinicalDiagnosisandTreatment,以下简称Gout-ITS系统)自动生成病例所需的领域知识及其特点,提出了语义树知识表示法和深度优先语义遍历算法。该算法可以有效地生成既符合学生的学习难度要求、又符合病理逻辑的、多样化不重复的病例。最后,将该算法与人工智能中的深度优先搜索算法[3]进行了比较,阐述了其中的不同之处。
The domain knowledge and its characters are discussed which is needed by the Gout-ITS to produce a typical cases, On this basis, the knowledge representation base of semantic tree and the depth first semantic traversal algorithm are brought forward, which are inherent in producing profitable cases. At last, the DFST algorithm and the depth first search algorithm of the AI are compared and the differences between them are showed.
出处
《计算机工程与设计》
CSCD
北大核心
2005年第12期3420-3422,3431,共4页
Computer Engineering and Design
关键词
智能教学系统
语义树
深度优先语义遍历
intelligent tutoring system
semantic tree
depth first semantic traversal
