Efficient processing of nested fuzzy SQL queries in a fuzzy database

被引:20
|
作者
Yang, Q [1 ]
Zhang, WN
Liu, CW
Wu, J
Yu, C
Nakajima, H
Rishe, ND
机构
[1] Univ Wisconsin, Dept Comp Sci, Platteville, WI 53818 USA
[2] Univ Texas, Dept Comp Sci, San Antonio, TX 78249 USA
[3] Depaul Univ, Sch Comp Sci Telecommun & Informat Sci, Chicago, IL 60604 USA
[4] Univ Illinois, Dept Elect Engn & Comp Sci, Chicago, IL 60607 USA
[5] OMRON Corp, Informat Technol Res Ctr, Verbal Interact Technol Lab, Nagaokakyo, Kyoto 6178510, Japan
[6] Florida Int Univ, Sch Comp Sci, High Performance Database Res Ctr, Miami, FL 33199 USA
基金
加拿大自然科学与工程研究理事会; 美国国家航空航天局; 美国国家科学基金会;
关键词
fuzzy database; fuzzy SOL; nested fuzzy query; query optimization; query transformation; possibility distribution; performance evaluation; fuzzy equijoin;
D O I
10.1109/69.971185
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In a fuzzy relational database where a relation is a fuzzy set of tuples and ill-known data are represented by possibility distributions, nested fuzzy queries can be expressed in the Fuzzy SOL language, as defined in [25], [23]. Although it provides a very convenient way for users to express complex queries, a nested fuzzy query may be very inefficient to process with the naive evaluation method. based on its semantics. In conventional databases, nested queries are unnested to improve the efficiency of their evaluation. In this paper, we extend the unnesting techniques to process several types of nested fuzzy queries. An extended merge-join is used to evaluate the unnested fuzzy queries. As shown by both theoretical analysis and experimental results, the unnesting techniques with the extended merge-join significantly improve the performance of evaluating nested fuzzy queries.
引用
收藏
页码:884 / 901
页数:18
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