DocumentCode :
1336238
Title :
An efficient evaluation of a fuzzy equi-join using fuzzy equality indicators
Author :
Zhang, Weining ; Wang, Ke
Author_Institution :
Texas Univ., San Antonio, TX, USA
Volume :
12
Issue :
2
fYear :
2000
Firstpage :
225
Lastpage :
237
Abstract :
Proposes a new measure of fuzzy equality (FE) comparison based on the similarity of possibility distributions. We define a type of fuzzy equi-join based on the new FE comparison and allow threshold values to be associated with predicates of the join condition. A sort-merge join algorithm based on a partial order of intervals is used to evaluate the fuzzy equi-join. In order for the evaluation to be efficient, we identify various mappings, called FE indicators, that determine appropriate intervals for fuzzy data with different characteristics. Experimental results from our preliminary simulation of the algorithm show a significant improvement of efficiency when FE indicators are used with the sort-merge join algorithm
Keywords :
database theory; deductive databases; fuzzy set theory; merging; possibility theory; relational databases; software performance evaluation; sorting; virtual machines; algorithm performance; efficiency; fuzzy data intervals; fuzzy equality indicators; fuzzy equi-join evaluation; fuzzy relational databases; interval partial order; mappings; possibility distribution similarity; predicates; simulation; sort-merge join algorithm; threshold values; Artificial intelligence; Computer Society; Data models; Database systems; Decision feedback equalizers; Fuzzy systems; Helium; Iron; Medical simulation; Relational databases;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/69.842264
Filename :
842264
Link To Document :
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