DocumentCode
2048960
Title
Fuzzy metaqueries for guiding the discovery process in KDD
Author
Cerquides, Jesus ; De Màntaras, Ramon López
Author_Institution
Artificial Intelligence Res. Inst., CSIC, Barcelona, Spain
Volume
3
fYear
1997
fDate
1-5 Jul 1997
Firstpage
1555
Abstract
This paper introduces the concept of fuzzy metaqueries and describes a framework for knowledge discovery in database (KDD) that has fuzzy metaqueries as its base. Fuzzy metaqueries are second order like fuzzy rules, very useful for the integration of inductive learning, deductive verification, human intuition and uncertainty handling
Keywords
deductive databases; fuzzy logic; knowledge acquisition; knowledge based systems; query processing; uncertainty handling; database query; fuzzy logic; fuzzy metaquery; fuzzy rules; knowledge acquisition; knowledge discovery; uncertainty handling; Artificial intelligence; Character generation; Councils; Data mining; Databases; Fuzzy logic; Fuzzy systems; Humans; Learning; Uncertainty;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 1997., Proceedings of the Sixth IEEE International Conference on
Conference_Location
Barcelona
Print_ISBN
0-7803-3796-4
Type
conf
DOI
10.1109/FUZZY.1997.619773
Filename
619773
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