Please use this identifier to cite or link to this item: https://doi.org/10.1109/69.842264
Title: An efficient evaluation of a fuzzy equi-join using fuzzy equality indicators
Authors: Zhang, W.
Wang, K. 
Keywords: Algorithm
Fuzzy databases
Fuzzy equality indicator
Fuzzy equi-join
Performance
Issue Date: 2000
Source: Zhang, W., Wang, K. (2000). An efficient evaluation of a fuzzy equi-join using fuzzy equality indicators. IEEE Transactions on Knowledge and Data Engineering 12 (2) : 225-237. ScholarBank@NUS Repository. https://doi.org/10.1109/69.842264
Abstract: We propose a new measure of fuzzy equality comparison based on the similarity of possibility distributions, we define a type of fuzzy equi-join based on the new fuzzy equality 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 fuzzy equality (FE) indicators, that will determine appropriate intervals for fuzzy data with different characteristics. Experiment 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. © 2000 IEEE.
Source Title: IEEE Transactions on Knowledge and Data Engineering
URI: http://scholarbank.nus.edu.sg/handle/10635/42314
ISSN: 10414347
DOI: 10.1109/69.842264
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