摘要
概念格是一种优良的形式化分析工具,已经广泛应用于知识发现和数据挖掘中。在大量研究中概念格基于精确的形式背景,即二值背景,而在实际中,形式背景中的信息往往是模糊、不确定的。本文将“模糊”引入概念格,定义了属性模糊概念格和其上的截运算,在概念格结点级上定义了两模糊参数α和δ,提出了从模糊概念格提取不确定规则、计算规则支持度、置信度的原则、方法,并给出了一个实例。
Concept lattice is a kind of excellent formal analyzed tool,has been widely applied in knowledge discovering and data mining. In many research Papers,concept lattice is based on precise context,also binary context. But in fact, information in context is usually fuzzy and indefinite. This paper introduces 'fuzzy' into concept lattice,defines fuzzy- attributes concept lattice and cut calculation,defines two fuzzy parameters α and δ on level of concept lattice node,pre- sents a method of abstracting assocication rules from fuzzy concept lattice and computing support and confidence of rules,also provides a case to illustrate the method.
出处
《计算机科学》
CSCD
北大核心
2005年第1期182-184,共3页
Computer Science
基金
国家自然科学基金<分布式概念格数学模型及算法研究>(60275022)
关键词
模糊概念格
知识发现
模糊语言变量
模糊参数
Fuzzy attribute concept lattice
Fuzzy language varible
Knowledge discovery
