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A Survey of Temporal Knowledge Discovery Paradigms and Methods
July/August 2002 (vol. 14 no. 4)
pp. 750-767

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.

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Index Terms:
Temporal data mining, time sequence mining, trend analysis, temporal rules, semantics of mined rules.
Citation:
John F. Roddick, Myra Spiliopoulou, "A Survey of Temporal Knowledge Discovery Paradigms and Methods," IEEE Transactions on Knowledge and Data Engineering, vol. 14, no. 4, pp. 750-767, July-Aug. 2002, doi:10.1109/TKDE.2002.1019212
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