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
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;
Conference_Titel :
Information Technology and Applications, 2009. IFITA '09. International Forum on
Conference_Location :
Chengdu
Print_ISBN :
978-0-7695-3600-2
DOI :
10.1109/IFITA.2009.242
