Title :
On some fuzzy extensions of association rules
Author :
Bosc, Patrick ; Pivert, Olivier
Author_Institution :
IRISA, ENSSAT, Lannion, France
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;
Conference_Titel :
IFSA World Congress and 20th NAFIPS International Conference, 2001. Joint 9th
Conference_Location :
Vancouver, BC
Print_ISBN :
0-7803-7078-3
DOI :
10.1109/NAFIPS.2001.944759
