Unnesting Fuzzy SQL Queries in Fuzzy Databases
The efficiency of processing fuzzy queries in fuzzy databases is a major concern. We provide techniques to unnest fuzzy queries (of two blocks) of type N, type J, type JA, and nested queries with quantifiers. We show that by unnesting the queries, efficiency can be improved significantly. The results obtained in the paper form the basis for unnesting fuzzy queries of arbitrary blocks in fuzzy databases.
KeywordsMain Memory Membership Degree Fuzzy Relation Satisfaction Degree Original Query
Unable to display preview. Download preview PDF.
- Codd EF. Extending the database relational model to capture more meaning. ACM TODS 1979Google Scholar
- Dayal U. Of nests and trees: a unified approach to processing queries that contain nested queries, aggregates, and quantifiers. VLDB 1987Google Scholar
- Ganski RA, Wong HKT. Optimization of nested SQL queries revisited. ACM SIGMOD 1987; 23–33Google Scholar
- Muralikrishna M. Improved unnesting algorithms for join aggregate SQL queries. VLDB 1992, Vancouver, Canada, pp 91–102Google Scholar
- Nakajima H. Development of an efficient fuzzy SQL for large scale fuzzy relational database. Proc. of 5th International Fuzzy Systems Association World Congress, 1993, pp 517–520Google Scholar
- Fuzzy LUNA - Fuzzy database system library user’s manual. Fuzzy LUNA - Fuzzy database system library reference manual. OMRON Corporation, 1992Google Scholar
- Salzberg B Tsukerman A, Gray J,Stewart M, Uren S, Vaughan B. Fast-Sort: a distributed single-input single-output external sort. SIGMOD 1990; 94–101Google Scholar
- Yang Q, Yu C, Nakajima H. A parallel scheme using the divide-andconquer method. SubmittedGoogle Scholar
- Zadeh LA. Fuzzy logic. IEEE Computer 1988; 83–93Google Scholar
- Zhang W, Yu C, Wang G, Pham T, Nakajima H. A relational model for imprecise queries. Int’l Symposium on Methodologies in Intelligent Systems, Trondheim, Norway, 1993Google Scholar