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Efficient processing of nested Fuzzy SQL queries in a fuzzy database

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7 Author(s)
Qi Yang ; Dept. of Comput. Sci., Wisconsin Univ., Platteville, WI, USA ; Weining Zhang ; Chengwen Liu ; Jing Wu
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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

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Knowledge and Data Engineering, IEEE Transactions on  (Volume:13 ,  Issue: 6 )