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