DocumentCode
2931150
Title
Speed up the execution efficiency of finding fuzzy frequent itemsets
Author
Hong Tzung-Pei ; Guo-Cheng Lan ; Yi-Hsin Lin ; Shing-Tai Pan
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
fYear
2012
fDate
16-18 Nov. 2012
Firstpage
279
Lastpage
282
Abstract
This paper proposes an efficient fuzzy mining approach, namely GDF, to speed up the execution efficiency of finding fuzzy frequent itemsets in a quantitative database. Unlike the existing approaches, the proposed GDF adopts the data-reduction strategy to effectively reduce the number of unpromising candidate fuzzy itemsets for mining. The experimental results on a synthetic dataset reveal that the proposed GDF approach could outperform the traditional fuzzy mining algorithm.
Keywords
data reduction; fuzzy set theory; GDF; candidate fuzzy itemsets; data-reduction strategy; execution efficiency; fuzzy frequent itemsets; fuzzy mining approach; quantitative database; Algorithm design and analysis; Association rules; Educational institutions; Itemsets; data mining; fuzzy data mining; fuzzy frequent itemset; pruning;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Theory and it's Applications (iFUZZY), 2012 International Conference on
Conference_Location
Taichung
Print_ISBN
978-1-4673-2057-3
Type
conf
DOI
10.1109/iFUZZY.2012.6409716
Filename
6409716
Link To Document