数据关联的粒化树描述方法

Descriptive Method on Data Association Based on Granulation Trees

为探讨数据关联问题,对数据集实施分层粒化处理,得到分层结构的粒化树.进而利用粒化树的层次信息和粒度的数值表示,并通过关联数据产生的数据联系,给出两棵粒化树之间数据关联的定义.文中视上近似为算子,借助上近似运算对应的粒,获得数据关联的判定定理,并基于粒度的数值信息判定关联紧密程度,形成数据关联的粒化树描述方法,其展示的粒化分层和粒度数值表示可看作粒计算研究的一种形式.实例的讨论表明粒化树方法的应用价值.

To study the data association, a data set is divided into different hierarchy granules. Consequently, a hierarchy structure called a granulation tree is obtained. Then, grounded on the granular hierarchy information in the granulation tree, the numerical representation of granularity and the data connections determined by association data, a definition of the data association between two granulation trees is introduced. In this paper, the upper approximation is taken as an operator. With the granule corresponding to the operation of the upper approximation, a theorem is established, and it is used to investigate whether two data are associated with each other. The investigation bases the close degree of the association on the numerical information of granular. Therefore, a method taking granulation trees as the basis to describe the data association is presented. The characteristics of the hierarchy granules and the numerical representation of granularity contained in the method provide a way of research on granular computing. The discussion on a specific example shows the application value of the granulation tree method.