Generalized association rule mining algorithms based on multidimensional data

被引：0
|
作者：
Zhang, Hong [1 ]
Zhang, Bo [1 ]
机构：
[1] China Univ Mining & Technol, Sch Comp Sci & Technol, Xuzhou 221008, Jiangsu, Peoples R China
来源：
RESEARCH AND PRACTICAL ISSUES OF ENTERPRISE INFORMATION SYSTEMS II, VOL 1 | 2008年 / 254卷
关键词：
multi-dimension; multidimensional data; date mining; generalized association rule; formalization;
D O I：
暂无
中图分类号：
F [经济];
学科分类号：
02 ;
摘要：
This paper proposes a new formalized definition of generalized association rule,based on Multidimensional data. The algorithms named BorderLHSs and GenerateLHSs-Rule are designed for generating generalized association rule from multi-level frequent item sets based on Multidimensional Data. Experiment shows that the algorithms proposed in this paper are more efficiency, generate less redundant rules and have good performance in flexibility, scalability and complexity.
引用
收藏
页码：337 / +
页数：3
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