DocumentCode :
2917412
Title :
An Incremental Updating Algorithm for Online Mining Association Rules
Author :
Yubo, Jia ; Yuntao, Duan ; Yongli, Wang
Author_Institution :
Inst. of Inf. & Electron, Zhejiang Sci-Tech Univ., Hangzhou, China
fYear :
2009
fDate :
7-8 Nov. 2009
Firstpage :
144
Lastpage :
148
Abstract :
Aimed at the limitation of the current FUP algorithm, which readily led to the low efficiency of frequent itemset of the updated database, a novel association rules mining algorithm named QAIS which is different from the classical dual phrase was proposed. On the basis of QAIS, an improved association rules mining algorithm named AIU was put forward further. AIU can efficiently maintain association rules when the transaction database was updated. At the same time, the minimum support and confidence were not changed. Experiments showed the proposed algorithm was appropriate to online association rules mining.
Keywords :
data analysis; data mining; QAIS algorithm; incremental updating algorithm; online association rule mining; transaction database; Algorithm design and analysis; Association rules; Computer science; Data mining; Electrons; Information systems; Itemsets; Iterative algorithms; Maintenance engineering; Transaction databases; association rules; data mining; incremental updating; online mining;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Web Information Systems and Mining, 2009. WISM 2009. International Conference on
Conference_Location :
Shanghai
Print_ISBN :
978-0-7695-3817-4
Type :
conf
DOI :
10.1109/WISM.2009.37
Filename :
5369434
Link To Document :
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