An Efficient Evaluation of a Fuzzy Equi-Join Using Fuzzy Equality Indicators
IEEE Transactions on Knowledge and Data Engineering
Mining Fuzzy Quantitative Association Rules
ICTAI '99 Proceedings of the 11th IEEE International Conference on Tools with Artificial Intelligence
Fuzzy domains with adaptable semantics in an object-relational DBMS
FQAS'11 Proceedings of the 9th international conference on Flexible Query Answering Systems
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Approaches are proposed to allow fuzzy terms to be interpreted according to the context within which they are used. Such an interpretation is natural and useful. A query-dependent interpretation is proposed to allow a fuzzy term to be interpreted relative to a partial answer of a query. A scaling process is used to transform a pre-defined meaning of a fuzzy term into on appropriate meaning in the given context. Sufficient conditions are given for a nested fuzzy query with RELATIVE quantifiers to be unnested for an efficient evaluation. An attribute-dependent interpretation is proposed to model the applications in which the meaning of a fuzzy term in an attribute must be interpreted with respect to values in other related attributes. Two necessary and sufficient conditions for a tuple to have a unique attribute-dependent interpretation are provided. We describe an interpretation system that allows queries to be processed based on the attribute-dependent interpretation of the data. Two techniques, grouping and shifting, are proposed to improve the implementation.