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Association Rules in Small Databases

Chapter
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2307)

Abstract

Accidents in nuclear power plants can cause environmental disasters and create personal, economical and ecological damage. Therefore, research into automatic surveillance and early nuclear accident de- tection has received much attention. To reduce nuclear accidents, re- liable information is needed for controlling, and/or preventing, such accidents. Hence, extracting useful patterns from limited data in nu- clear power plants is very important, and is imperative for the pur- pose of safety. This kind of knowledge is generally obtained from theoretical, experimental, and real data. However, nuclear accidents rarely occur, and we may discover nothing from the accident database in a plant. Therefore, reliable mining of an accident database in a nuclear power plant would require dependence upon external data as well.

Keywords

Nuclear Power Plant Association Rule Frequent Itemsets External Knowledge External Data 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2002

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