DocumentCode
3285290
Title
Association Rules Algorithm Research in Optical Warning System
Author
Chaoju, Hu ; Min, Peng
Author_Institution
Inf. Process. Libr., North China Electr. Power Univ. of Comput. Sci. & Technol., Baoding, China
Volume
3
fYear
2009
fDate
15-17 May 2009
Firstpage
189
Lastpage
192
Abstract
Mining association rules with multiple minimum supports is an important research aspect of data mining. In this paper we propose a database partition method to mine the frequent item sets, and use MIS-tree to store the crucial information about frequent patterns. We use the CFP-growth algorithm to mine local frequent patterns and insert them into the global frequent pattern. The experiment on OASN shows that the method is effective to predict the optical warning level.
Keywords
data mining; database management systems; optical computing; trees (mathematics); MIS-tree; association rules algorithm; data mining; database partition method; optical warning system; Alarm systems; Algorithm design and analysis; Application software; Association rules; Chaos; Data mining; Information technology; Partitioning algorithms; Spatial databases; Transaction databases; CFP-growth; MIS-tree; database partition; frequent pattern;
fLanguage
English
Publisher
ieee
Conference_Titel
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location
Chengdu
Print_ISBN
978-0-7695-3600-2
Type
conf
DOI
10.1109/IFITA.2009.242
Filename
5232092
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