Integrating fuzziness into OLAP for multidimensional fuzzy association rules mining

被引：0

作者：

Alhajj, R ^{[1
]}

Kaya, M ^{[1
]}

机构：

[1] Univ Calgary, ADSA Lab, Calgary, AB, Canada

来源：

THIRD IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS | 2003年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper contributes to the ongoing research on multidimensional online association rules mining by proposing a general architecture that utilizes a fuzzy data cube for knowledge discovery. Three different methods are introduced to mine fuzzy association rules in the constructed fuzzy data cube, namely single dimension, multidimensional and hybrid association rules mining. Experimental results obtained for each of the three methods on the adult data of the United States census in 2000 show their effectiveness and applicability.

引用

页码：469 / 472

页数：4

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