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
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