DocumentCode :
787151
Title :
A survey of temporal knowledge discovery paradigms and methods
Author :
Roddick, John F. ; Spiliopoulou, Myra
Author_Institution :
Sch. of Informatics & Eng., Flinders of Univ. of South Australia, Adelaide, SA, Australia
Volume :
14
Issue :
4
fYear :
2002
Firstpage :
750
Lastpage :
767
Abstract :
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.
Keywords :
data mining; database theory; temporal databases; time series; very large databases; data sets; large databases; rule semantics; temporal data mining; temporal databases; temporal knowledge discovery paradigms; temporal rules; time sequence mining; trend analysis; Artificial intelligence; Association rules; Computer industry; Data mining; Databases; Helium; Mining industry; Prototypes; Time varying systems; Voting;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/TKDE.2002.1019212
Filename :
1019212
Link To Document :
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