Mining direct and indirect fuzzy sequential patterns in large transaction databases

被引：0
|
作者：
Ouyang, Weimin [1 ,2 ]
Huang, Qinhua [2 ]
机构：
[1] Shanghai Univ Sport, Dept Management, Shanghai 200438, Peoples R China
[2] Shanghai Univ, Sch Comp Engn & Sci, Shanghai 200072, Peoples R China
来源：
ADVANCED INTELLIGENT COMPUTING THEORIES AND APPLICATIONS: WITH ASPECTS OF CONTEMPORARY INTELLIGENT COMPUTING TECHNIQUES | 2007年 / 2卷
关键词：
sequential pattern; indirect; fuzzy logic;
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：
Sequential pattern is an important research topic in data mining and knowledge discovery. Traditional algorithms for mining sequential patterns are built on the binary attributes databases, which has two limitations. First, it can not concern quantitative attributes; second, only direct sequential patterns are discovered. Mining fuzzy sequential patterns has been proposed to address the first limitation. In this paper, we put forward a discovery algorithm for mining indirect sequential patterns to resolve the second limitation, and a discovery algorithm for mining both direct and indirect fuzzy sequential patterns by combining these two approaches.
引用
收藏
页码：180 / +
页数：2
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