DocumentCode
3373746
Title
Mining fuzzy quantitative association rules
Author
Zhang, Weining
Author_Institution
Div. of Comput. Sci., Texas Univ., San Antonio, TX, USA
fYear
1999
fDate
1999
Firstpage
99
Lastpage
102
Abstract
Given a relational database and a set of fuzzy terms defined for some attributes we consider the problem of mining fuzzy quantitative association rules that may contain crisp values, intervals, and fuzzy terms in both antecedent and consequent. We present an algorithm extended from the equi-depth partition (EDP) algorithm for solving this problem. Our approach combines interval partition with pre-defined fuzzy terms and is more general
Keywords
data mining; database theory; fuzzy logic; relational databases; crisp values; equi-depth partition algorithm; fuzzy quantitative association rule mining; fuzzy terms; interval partition; relational database; Association rules; Clustering algorithms; Computer science; Data mining; Fuzzy sets; Marine vehicles; Marketing management; Read only memory; Relational databases; Transaction databases;
fLanguage
English
Publisher
ieee
Conference_Titel
Tools with Artificial Intelligence, 1999. Proceedings. 11th IEEE International Conference on
Conference_Location
Chicago, IL
ISSN
1082-3409
Print_ISBN
0-7695-0456-6
Type
conf
DOI
10.1109/TAI.1999.809772
Filename
809772
Link To Document