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Modeling Fuzzy Information in the EER and Nested Relational Database Models

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Flexible Databases Supporting Imprecision and Uncertainty

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 203))

Abstract

A major goal for database research has been the incorporation of additional semantics into database models. It is recognized that the relational database model has semantic and structured drawbacks when it comes to modeling some emerging applications such as computer aided design (CAD), geographical information systems (GIS), and artificial intelligence. In response to this problem, some attempts to relax the first normal form (1NF) limitation, which is the most fundamental normalization constraint in the relational databases, are made and one kind of data model, called non-first normal (or nested) relational database model, has been introduced. In common sense, the nested relational database model means that attribute values in the relational instances are either atomic or set-valued and even relations themselves. In addition, the next generation of database models takes the form of rich data models such as the object-oriented database model and the semantic (conceptual) data models.

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Ma, Z.M. (2006). Modeling Fuzzy Information in the EER and Nested Relational Database Models. In: Bordogna, G., Psaila, G. (eds) Flexible Databases Supporting Imprecision and Uncertainty. Studies in Fuzziness and Soft Computing, vol 203. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-33289-8_5

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  • DOI: https://doi.org/10.1007/3-540-33289-8_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-33288-6

  • Online ISBN: 978-3-540-33289-3

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