%0 Journal Article
%T 数据的动态挖掘与P-增广矩阵关系<br>Relationships between dynamic data mining and P-augmented matrix
%A 郭华龙
%A 任雪芳
%A 张凌&lt
%A br&gt
%A GUO Hua-long
%A REN Xue-fang
%A ZHANG Ling
%J 山东大学学报（理学版）
%D 2016
%R 10.6040/j.issn.1671-9352.0.2016.200
%X 摘要： P-增广矩阵是通过利用P-集合的结构与动态特征,改进普通增广矩阵A*提出的。P-增广矩阵是由内P-增广矩阵A(-overF)与外P-增广矩阵AF构成的矩阵对,或者(A(-overF),AF)是P-增广矩阵。在一定条件下,P-增广矩阵(A(-overF),AF)被还原成普通增广矩阵A*。利用P-增广矩阵的结构与动态特征,给出数据的动态挖掘研究及其与P-增广矩阵的关系。提出数据的动态挖掘的内P-增广矩阵判定定理,外P-增广矩阵判定定理与P-增广矩阵判定定理,给出数据的动态挖掘的P-增广矩阵准则,利用这些理论结果,给出一个简单应用。<br>Abstract: P-augmented matrix is proposed by adopting the structures and dynamic characteristics of packet sets to improve ordinary augmented matrix A*. P-augmented matrix consists of internal P-augmented matrix A(-overF) and outer P-augmented matrix AF, denoted by(A(-overF),AF). Under some certain conditions, P-augmented matrix can be reduced into ordinary augmented matrix A*. By using the structures and dynamic characteristics of P-augmented matrix, the research of dynamic data mining is carried out. Several relationships, theorems and criterion are obtained as follows: the relationships between dynamic data mining and P-augmented matrix; the internal P-augmented matrix decision theorem, the outer P-augmented matrix decision theorem and the P-augmented matrix decision theorem for data dynamic mining; the P-augmented matrix criterion for dynamic data mining. Finally, these results are verified by an application
%K P-集合
%K 数据动态挖掘
%K 挖掘准则
%K 判定定理
%K P-增广矩阵
%K &lt
%K br&gt
%K P-sets
%K dynamic data mining
%K mining criterion
%K decision theorem
%K P-augmented matrix
%U http://lxbwk.njournal.sdu.edu.cn/CN/10.6040/j.issn.1671-9352.0.2016.200