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Fuzzy data exchange
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AI
DOI：10.1016/j.fss.2015.12.004.png)
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Abstract
En 中文
Data exchange is the problem of transforming data that conforms to one source schema into data that conforms to a target schema that reflects the source data as accurately as possible and in a way that is consistent with various dependencies. In a landmark paper, Fagin et al. have proposed a declarative, purely logical approach to this task. Since then, data exchange has been intensively studied in the database research community. In this paper we extend the classical data exchange approach of Fagin et al. to fuzzy data exchange as a framework concerned with the transformation of fuzzy data. We show that the most important properties of data exchange are preserved in this new setting. Moreover, the relation of fuzzy data exchange to the classical setting, probabilistic data exchange and fuzzy logic is studied. (C) 2016 Elsevier B.V. All rights reserved.
Keywords:
Fuzzy sets
Data exchange
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