DocumentCode :
1553400
Title :
Efficient processing of nested Fuzzy SQL queries in a fuzzy database
Author :
Yang, Qi ; Zhang, Weining ; Liu, Chengwen ; Wu, Jing ; Yu, Clement ; Nakajima, Hiroshi ; Rishe, Naphtali David
Author_Institution :
Dept. of Comput. Sci., Wisconsin Univ., Platteville, WI, USA
Volume :
13
Issue :
6
fYear :
2001
Firstpage :
884
Lastpage :
901
Abstract :
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 SQL language. 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
Keywords :
SQL; fuzzy set theory; merging; query processing; relational databases; Fuzzy SQL language; extended merge-join; fuzzy relational database; fuzzy tuple set; nested fuzzy SQL query processing; possibility distributions; unnesting techniques; Computer Society; Computer science; Data models; Database systems; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Performance analysis; Query processing; Relational databases;
fLanguage :
English
Journal_Title :
Knowledge and Data Engineering, IEEE Transactions on
Publisher :
ieee
ISSN :
1041-4347
Type :
jour
DOI :
10.1109/69.971185
Filename :
971185
Link To Document :
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