DocumentCode :
2308141
Title :
A two-phase fuzzy mining approach
Author :
Lin, Chun-Wei ; Hong, Tzung-Pei ; Lu, Wen-Hsiang
Author_Institution :
Dept. of Comput. Sci. & Inf. Eng., Nat. Cheng Kung Univ., Tainan, Taiwan
fYear :
2010
fDate :
18-23 July 2010
Firstpage :
1
Lastpage :
5
Abstract :
In this paper, we propose a two-phase fuzzy mining approach based on a tree structure to discover fuzzy frequent itemsets from a quantitative database. A simple tree structure called the upper-bound fuzzy frequent-pattern tree (abbreviated as UBFFP tree) is designed to help achieve the purpose. The two-phase fuzzy mining approach can easily derive the upper-bound fuzzy supports of itemsets through the tree and prune unpromising itemsets in the first phase, and then finds the actual frequent fuzzy itemsets in the second phase. Experimental results also show the good performance of the proposed approach.
Keywords :
data mining; fuzzy set theory; tree data structures; UBFFP tree; fuzzy frequent itemset; quantitative database; tree structure; two-phase fuzzy mining; upper-bound fuzzy frequent-pattern tree; Algorithm design and analysis; Association rules; Computer science; Construction industry; Itemsets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems (FUZZ), 2010 IEEE International Conference on
Conference_Location :
Barcelona
ISSN :
1098-7584
Print_ISBN :
978-1-4244-6919-2
Type :
conf
DOI :
10.1109/FUZZY.2010.5584373
Filename :
5584373
Link To Document :
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