DocumentCode
506925
Title
An Efficient Algorithm of Mining Association Rules Based on Digital Pure Subset
Author
Liu, Yu-Lu ; Fang, Gang ; Xiong, Jiang ; Wu, Yuan-bin
Author_Institution
Coll. of Math & Comput. Sci., Chongqing Three Gorges Univ., Chongqing, China
Volume
2
fYear
2009
fDate
14-16 Aug. 2009
Firstpage
43
Lastpage
46
Abstract
This paper proposes an efficient algorithm of double search mining association rules based on digital pure subset, which uses the method of forming digital pure subset of transaction to generate candidate itemsets, and uses digital character to reduce the number of scanned transactions when computing support of itemsets after these transactions are turned into digital transaction by binary. In addition, the algorithm uses logical operation to compute support of candidate itemsets, and uses the way of ascending value to form pure subset of digital transaction via maximal and minimal transactions synchronously close to intermediate value, which is different from traditional algorithms of double search mining association rules. The experiment indicates that the efficiency of the algorithm is faster and more efficient than presented algorithms of double search mining association rules.
Keywords
data mining; candidate itemsets; digital character; digital pure subset; digital transaction; double search mining association rules; maximal transactions; minimal transactions; Association rules; Character generation; Computer science; Data mining; Databases; Desktop publishing; Educational institutions; Electronic mail; Fuzzy systems; Itemsets; ascending value; association rules; digital character; digital pure subset; double search;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems and Knowledge Discovery, 2009. FSKD '09. Sixth International Conference on
Conference_Location
Tianjin
Print_ISBN
978-0-7695-3735-1
Type
conf
DOI
10.1109/FSKD.2009.136
Filename
5358883
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