【作者】 张素兰； 张继福；

【Author】 Zhang Sulan Zhang Jifu ( Department of Computer Science and Engineering,Taiyuan Heavy Machinery Institute, 030024) ( School of Electromechanical Engineering, Beijing Institute of Technology, 100081)

【机构】 太原重型机械学院计算机科学与工程系；

【摘要】 概念格体现了概念聚类和提升的过程,是可以将知识分类的有效的形式化工具．粗集理论是进行分析模糊性不确定性数据的有力工具,可以利用不可分辨关系和不可分辨类对不确定性数据进行分类。因此对于数据仓库中各种不同类型的海量数据,融合这两种理论可以提高分类知识挖掘的效率与准确程度,有效地指导高级决策管理。本文针对数据仓库数据的特点,提出了一种融合粗集理论和概念格理论的分类知识挖掘模型。更多还原

【Abstract】 According to the data characteristic in the data warehouse , this paper presents the merge theory of rough set and concept lattice. Concept lattice, an efficient formal analysis tool . can classify the data through the relation of concept intension and concept extension .Rough set is a very useful tool to analysis uncertain and vague data and can be used to classify data with the specific upper and lower approximate set. Merging the two theory will improve the efficiency and reliability of the classification knowledge and guide the decision-making Management. This paper also presents one classification mining model.更多还原