摘要
MKL是知识获取系统NDKAS中实现的一个元知识学习算法,它在分类及抽象的基础上归纳出二叉树结构的元知识,用以有效地组织知识库中的规则.MKL生成的元知识满足元知识的基本性质.本文给出了MKL的算法描述,基本性质的满足性证明及算法的应用例子.
MKL,an algorithm for meta-knowledge learning,is presented in NDKAS,which is a knowledge acquisition system.On the basis of classification and abstraction, it can induces meta-knowledge which is used to effectively organize rules in knowledge base in binary-tree structure,which satisfies the essential properties of meta-knowledge.The structural representation of meta-knowledge,the algorithm description of MKL and the proof of satisfaction of the essential properties are given in the paper.An example of MKL application is also described.
出处
《软件学报》
EI
CSCD
北大核心
1995年第5期316-320,共5页
Journal of Software
基金
国家自然科学基金
关键词
元知识学习
知识获取
专家系统
二叉树
Concept acquisition,experience knowledge classification,meta-knowledge learning.