Descriptive Method on Data Association Based on Granulation Trees
YAN Shuo1, YAN Lin2
1.School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044 2.College of Computer and Information Engineering, Henan Normal University, Xinxiang 453007
Abstract：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.
闫硕，闫林. 数据关联的粒化树描述方法[J]. 模式识别与人工智能, 2015, 28(12): 1057-1066.
YAN Shuo , YAN Lin. Descriptive Method on Data Association Based on Granulation Trees. , 2015, 28(12): 1057-1066.
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