DocumentCode
670237
Title
Fast evaluation of t-norms for fuzzy association rules mining
Author
Burda, Michal
Author_Institution
Inst. for Res. & Applic. of Fuzzy Modeling, Univ. of Ostrava, Ostrava, Czech Republic
fYear
2013
fDate
19-21 Nov. 2013
Firstpage
465
Lastpage
470
Abstract
The aim of this paper is to present a bitwise approach on evaluation of fuzzy t-norms. T-norms are functions that generalize the notion of conjunction, and as such play an important role in fuzzy association rule mining process. Efficient algorithms for batch evaluation of the most common t-norms is proposed that minimizes computation time as well as memory space requirements at the cost of user-adjustable loss of precision of the membership degrees.
Keywords
data mining; fuzzy set theory; batch evaluation; bitwise approach; fuzzy association rule mining process; fuzzy t-norms; membership degrees; memory space requirements; user-adjustable precision loss; Arrays; Association rules; Computational intelligence; Computers; Fuzzy sets; Indexes; Random access memory;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence and Informatics (CINTI), 2013 IEEE 14th International Symposium on
Conference_Location
Budapest
Print_ISBN
978-1-4799-0194-4
Type
conf
DOI
10.1109/CINTI.2013.6705242
Filename
6705242
Link To Document