知识的属性依赖挖掘与识别  

Attribute dependence mining and recognition of knowledge

作　　者：刘若慧[1] 鄢川江[2,3] 史开泉[2] 

机构地区：[1]黄淮学院计算机科学系,河南驻马店463000 [2]山东大学数学与系统科学学院,山东济南250100 [3]黄淮学院数学系,河南驻马店463000

出　　处：《山东大学学报（理学版）》2008年第11期85-90,共6页Journal of Shandong University(Natural Science)

基　　金：山东省自然科学基金资助项目(Y2007H02);河南省教育厅自然科学研究基金资助项目(2008C120002)

摘　　要：利用属性集α内被补充属性,知识[x]内的元素个数被减少;利用属性集α内的部分属性被删除,知识[x]内的元素个数被增加的两个特性。给出阶梯知识,阶梯知识生成,知识属性依赖的概念,提出知识的属性依赖挖掘定理,知识的属性依赖挖掘-状态识别准则,给出知识的属性依赖挖掘的应用。If there are new attributes supplemented to α, then the elements in [ x ] will decrease; if some attributes in α were deleted, then the elements in [ x ] will increase. By using the above two characteristics, the concepts of ladder knowledge, the generation of ladder knowledge and the attribute dependence of knowledge were presented, the attribute dependence mining theorem of knowledge and the attribute dependence mining-state recognition criterion of knowledge were proposed, and the applications of attribute dependence mining of knowledge were also given.

关 键 词：阶梯知识 属性依赖 依赖挖掘 单位圆定理 挖掘定理 

分 类 号：O159[理学—数学]