The mining of fuzzy gradient in the case of materialized cube

Author

Liu, Yubao ; Yin, Jian

Author_Institution

Dept. of Comput. Sci., Sun Yat-Sen Univ., Guangzhou

fYear

2005

fDate

21-23 Sept. 2005

Firstpage

93

Lastpage

97

Abstract

The mining of cube gradient is a new research problem in the data mining community. It is an extension of the traditional association rules mining in the data cube and its purpose is to mine the changes of measures in a multidimensional space. However, previous works explore for cube gradients with raw number, and the semantics of the changes of cube gradients, such as high or low, are not clear and those are not easy to be understood for the decision makers. In this paper, the fuzzy gradient mining problem with fuzzy constraint sets is presented. The mining algorithm, MFG, for the problem in the case of materialized cube is presented. In MFG, the condensed cube technology is used to reduce the searching space of the mining algorithm. The performance tests based on the synthesized data sets show the mining algorithm is effective and scalable with the fuzzy constraint sets

Keywords

constraint theory; data mining; decision making; fuzzy set theory; association rules; data mining; decision makers; fuzzy constraint set; fuzzy gradient mining problem; materialized cube technology; synthesized data set; Association rules; Computer aided software engineering; Computer science; Data mining; Extraterrestrial measurements; Fuzzy sets; Multidimensional systems; Space technology; Sun; Testing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computer and Information Technology, 2005. CIT 2005. The Fifth International Conference on

Conference_Location

Shanghai

Print_ISBN

0-7695-2432-X

Type

conf

DOI

10.1109/CIT.2005.188

Filename

1562634