摘要
模糊Horn子句规则可以用自然语言来表达人类知识。但是,发现模糊Horn子句规则及其蕴含度是比较困难的。该文从逻辑的观点出发,定义模糊Horn子句规则、支持度、蕴含度及其相关概念,分析模糊Horn子句规则发现的步骤,并给出发现算法的形式化描述。该算法结合了模糊Horn子句逻辑概念和Apriori发现算法,从给定的数量型数据库中发现模糊Horn子句规则。
Fuzzy Horn clause rules can be used to represent human knowledge in terms of natural language. However, it is more difficult to discover fuzzy Horn clause rules and its implication degree. From the logical point of view, in this paper, fuzzy Horn clause rules, support degree, implication degree and related concepts are defined. The processes of mining fuzzy Horn clause rules are analyzed, and the formal algorithm is proposed. This algorithm integrates the concepts of fuzzy Horn clause logic and the Apriori algorithm to find fuzzy Horn clause rules from quantitative databases.
出处
《计算机工程》
CAS
CSCD
北大核心
2009年第2期184-186,共3页
Computer Engineering
关键词
模糊Horn子句规则
支持度
蕴含度
定量数据库
fuzzy Horn clause rules
support degree
implication degree
quantitative databases