DocumentCode :
324648
Title :
A new approach to the filtering of ill-known data
Author :
Bosc, Patrick ; Pivert, Olivier
Author_Institution :
ENSSAT, IRISA, France
Volume :
2
fYear :
1998
fDate :
4-9 May 1998
Firstpage :
1302
Abstract :
In this paper, the issue of querying databases containing ill-known values is addressed. A new type of query is introduced based on criteria applying to the representations of ill-known data. In the regular possibilistic framework, the only authorized selection criteria concern the value that an item can take. We introduce a new querying framework in order to exploit some concepts which are part of the model used for representing ill-known data, and which concern the qualification of imprecision/uncertainty. The representation-based querying framework defined in this paper constitutes the first step to the introduction of an explicit manipulation of the concepts of imprecision and/or uncertainty into a database query language
Keywords :
data structures; fuzzy logic; fuzzy set theory; possibility theory; query processing; relational databases; uncertainty handling; data representation; database query language; database querying; fuzzy database; fuzzy logic; fuzzy set theory; ill-known data filtering; possibility distribution; uncertainty handling; Boolean functions; Database languages; Database systems; Filtering; Fuzzy sets; Iris; Qualifications; Testing; Uncertainty;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Fuzzy Systems Proceedings, 1998. IEEE World Congress on Computational Intelligence., The 1998 IEEE International Conference on
Conference_Location :
Anchorage, AK
ISSN :
1098-7584
Print_ISBN :
0-7803-4863-X
Type :
conf
DOI :
10.1109/FUZZY.1998.686307
Filename :
686307
Link To Document :
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