Mining frequent ordered patterns

被引：0
|
作者：
Deng, ZH [1 ]
Ji, CR
Zhang, M
Tang, SW
机构：
[1] Peking Univ, Sch Elect Engn & Comp Sci, Beijing 100871, Peoples R China
[2] Peking Univ, Natyl Lab Machine Percept, Beijing 100871, Peoples R China
来源：
ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING, PROCEEDINGS | 2005年 / 3518卷
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：
Mining frequent patterns has been studied popularly in data mining research. All of previous studies assume that items in a pattern are unordered. However, the order existing between items must be considered in some applications. In this paper, we first give the formal model of ordered patterns and discuss the problem of mining frequent ordered patterns. Base on our analyses, we present two efficient algorithms for mining frequent ordered patterns. We also present results of applying these algorithms to a synthetic data set, which show the effectiveness of our algorithms.
引用
收藏
页码：150 / 154
页数：5
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