A New Fuzzy Association Rules Mining in Data Streams

被引：0
|
作者：
Shen, Liangzhong [1 ]
Liu, Shihua [2 ]
机构：
[1] Wenzhou Univ, City Coll, Informat Management Dept, Wenzhou, Peoples R China
[2] Wenzhou Univ, City Coll, Dept Comp Sci, Wenzhou, Peoples R China
来源：
ADVANCED TECHNOLOGY IN TEACHING - PROCEEDINGS OF THE 2009 3RD INTERNATIONAL CONFERENCE ON TEACHING AND COMPUTATIONAL SCIENCE (WTCS 2009), VOL 2: EDUCATION, PSYCHOLOGY AND COMPUTER SCIENCE | 2012年 / 117卷
关键词：
Fuzzy Association Rules; Data Stream; Change Detection;
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：
In this paper, a novel fuzzy ARM algorithm called FFI_Stream is presented to tackle quantitative attributes in data streams and some techniques are proposed in the algorithm. Both synthetic and real datasets are used to evaluate the performance of the proposed algorithm. The experimental results show both the effectiveness and efficiency of the proposed algorithm. In comparison with the discrete method, the proposed algorithm using fuzzy sets and MFB_measure gets a trade-off between the number of interesting rules and efficiency.
引用
收藏
页码：163 / +
页数：2
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