DocumentCode
3182502
Title
Mining complete fuzzy frequent itemsets by tree structures
Author
Hong, Tzung-Pei ; Lin, Tsung-Ching ; Tsung-Ching Lin
Author_Institution
Dept. of Comput. Sci. & Inf. Eng., Nat. Univ. of Kaohsiung, Kaohsiung, Taiwan
fYear
2010
fDate
10-13 Oct. 2010
Firstpage
563
Lastpage
567
Abstract
In this paper, we attempt to extend the fuzzy FP-tree mining process to mine all fuzzy frequent itemsets, instead of only the representative linguistic terms, from a set of quantitative transactions. A multiple fuzzy-term FP (MFFP) tree with the consideration of fuzzy operations is proposed to help the execution of the fuzzy mining process. The corresponding MFFP-growth mining algorithm is also designed to derive all fuzzy frequent itemsets from the tree structure by fuzzy operations. Experimental results also show the performance of the proposed approach.
Keywords
data mining; fuzzy set theory; tree data structures; fuzzy frequent itemsets mining; multiple fuzzy term FP tree mining process; tree structure; Association rules; Itemsets; fuzzy data mining; fuzzy frequent itemset; fuzzy region; fuzzy set; quantitative value;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems Man and Cybernetics (SMC), 2010 IEEE International Conference on
Conference_Location
Istanbul
ISSN
1062-922X
Print_ISBN
978-1-4244-6586-6
Type
conf
DOI
10.1109/ICSMC.2010.5642016
Filename
5642016
Link To Document