DocumentCode
3400195
Title
On some fuzzy extensions of association rules
Author
Bosc, Patrick ; Pivert, Olivier
Author_Institution
IRISA, ENSSAT, Lannion, France
Volume
2
fYear
2001
fDate
25-28 July 2001
Firstpage
1104
Abstract
This paper discusses the semantics of two fuzzy extensions of the classical concept of an association rule. Both extensions are based on the aggregation of sufficiently close data into fuzzy sets, by means of user-defined fuzzy partitions of the domains, thus leading to fuzzy generalized association rules. The first approach is based on fuzzy cardinalities whereas the second one relies on gradual rules. The issue related to the evaluation of the validity of such rules is discussed and the principles of two discovery algorithms are outlined
Keywords
data mining; database theory; fuzzy set theory; very large databases; association rule; data mining; fuzzy cardinalities; fuzzy extensions; fuzzy generalized association rules; fuzzy set theory; knowledge discovery; large databases; semantics; user-defined fuzzy partitions; Aggregates; Association rules; Data mining; Databases; Frequency; Fuzzy logic; Fuzzy sets; Labeling; Natural languages; Partitioning algorithms;
fLanguage
English
Publisher
ieee
Conference_Titel
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-7078-3
Type
conf
DOI
10.1109/NAFIPS.2001.944759
Filename
944759
Link To Document