Mining temporal patterns from sequence database of interval-based events

被引：0
|
作者：
Chen, Yen-Liang [1 ]
Wu, Shin-Yi [1 ]
机构：
[1] Natl Cent Univ, Dept Informat Management, Chungli 320, Taiwan
来源：
FUZZY SYSTEMS AND KNOWLEDGE DISCOVERY, PROCEEDINGS | 2006年 / 4223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：
Sequential pattern mining is one of the important techniques of data mining to discover some potential useful knowledge from large databases. However, existing approaches for mining sequential patterns are designed for point-based events. In many applications, the essence of events are interval-based, such as disease suffered, stock price increase or decrease, chatting etc. This paper presents a new algorithm to discover temporal pattern from temporal sequences database consisting of interval-based events.
引用
收藏
页码：586 / 595
页数：10
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