摘要
概念格和粗糙集是数据挖掘中对数据进行分析与处理的两个有力工具,它们在数据分析方面有相似之处。通过运用概念格刻画粗糙集的一些概念与性质给二者建立了联系。指出了概念格每个结点都是粗糙集中一个等价类,并借鉴粗糙集的思想,提出了在概念格中进行概念近似的方法。同时使用概念格中的概念重新描述了粗糙集的上下近似,最后通过事例将粗糙集中改进的区分矩阵运用于概念格中的属性约简,从而减少了区别矩阵的存储空间,并同时减少了区别矩阵的计算量,真正从一定意义上结合了二者的优点。
Concept lattice and rough sets are two powerful tools in data mining for data analysis and processing,there are some similar parts between them of data analysis.Some relations are established by depicting some concepts and characters of rough sets usings concept lattice.Indicate that every node of concept lattice is an equivalence class of rough set,and rough set use for reference,bring forward the method of concept approximation in concept lattice.At the same time,the upper and lower approximations are red scribed by use of some concepts of concept lattice,finally,the improved discernibility matrix was used to the attribute reduction with an example.Ac-cordingly the memories of the discernibility matrix reduce,so does the quantity of calculating.Strong points between them are combined.
出处
《计算机工程与设计》
CSCD
北大核心
2008年第6期1423-1425,共3页
Computer Engineering and Design
关键词
形式背景
概念格
粗糙集
区别矩阵
等价类
属性约简
概念近似
formal context
concept lattice
rough sets
discernibility matrix
equivalence classes
attribute reduction
concept ap-proximation
