A survey of temporal knowledge discovery paradigms and methods

被引:191
作者
Roddick, JF
Spiliopoulou, M
机构
[1] Flinders Univ S Australia, Sch Informat & Engn, Adelaide, SA 5001, Australia
[2] Leipzip Grad Sch, D-04109 Leipzig, Germany
关键词
temporal data mining; time sequence mining; trend analysis; temporal rules; semantics of mined rules;
D O I
10.1109/TKDE.2002.1019212
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With the increase in the size of data sets, data mining has recently become an important research topic and is receiving substantial interest from both academia and industry. At the same time, interest in temporal databases has been increasing and a growing number of both prototype and implemented systems are using an enhanced temporal understanding to explain aspects of behavior associated with the implicit time-varying nature of the universe. This paper investigates the confluence of these two areas, surveys the work to date, and explores the issues involved and the outstanding problems in temporal data mining.
引用
收藏
页码:750 / 767
页数:18
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