DocumentCode :
3067257
Title :
A Decomposition Approach for Mining Frequent Itemsets
Author :
Huang, Jen-Peng ; Lan, Guo-Cheng ; Kuo, Huang-Cheng ; Hong, Tzung-Pei
Author_Institution :
Southern Taiwan Univ. of Technol., Tainan
Volume :
2
fYear :
2007
fDate :
26-28 Nov. 2007
Firstpage :
605
Lastpage :
608
Abstract :
In this paper, instead of proposing the fastest mining algorithm in the world, we present a new approach in mining association rules. We propose a new algorithm - GRA (Gradational Reduction Approach). It adopts three mechanisms to increase the performance of mining. First, GRA algorithm uses a hash based technique, Hash MAP, which is similar to Hash Table to increase the access efficiency. Second, GRA algorithm uses an infrequent itemsets filtering mechanism to avoid generating a great deal of infrequent sub-itemsets of transaction records. Third, in order to reduce the size of database, GRA algorithm uses gradational reduction mechanism which uses the frequent itemsets as the information of filtration mechanisms to erase the infrequent items from database at every phase. GRA algorithm can decrease a large number of non-frequent itemsets and increase the utility rate of memory.
Keywords :
data mining; association rules mining; decomposition approach; fast mining algorithm; frequent itemsets mining; gradational reduction approach; Association rules; Computer science; Data mining; Electronic mail; Filtering algorithms; Filtration; Information analysis; Information management; Itemsets; Transaction databases;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Intelligent Information Hiding and Multimedia Signal Processing, 2007. IIHMSP 2007. Third International Conference on
Conference_Location :
Kaohsiung
Print_ISBN :
978-0-7695-2994-1
Type :
conf
DOI :
10.1109/IIH-MSP.2007.11
Filename :
4457782
Link To Document :
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