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