Normalization and lossless join decomposition of similarity-based fuzzy relational databases

Date

2004-10-01

Author

Bahar, O
Yazıcı, Adnan

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Fuzzy relational database models generalize the classical relational database model by allowing uncertain and imprecise information to be represented and manipulated. In this article, we introduce fuzzy extensions of the normal forms for the similarity-based fuzzy relational database model. Within this framework of fuzzy data representation, similarity, conformance of tuples, the concept of fuzzy functional dependencies, and partial fuzzy functional dependencies are utilized to define the fuzzy key notion, transitive closures, and the fuzzy normal forms. Algorithms for dependency preserving and lossless join decompositions of fuzzy relations are also given. We include examples to show how normalization, dependency preserving, and lossless join decomposition based on the fuzzy functional dependencies of fuzzy relation are done and applied to some real-life applications. (C) 2004 Wiley Periodicals, Inc.

Subject Keywords

Theoretical Computer Science, Human-Computer Interaction, Software, Artificial Intelligence

URI

https://hdl.handle.net/11511/62697

Journal

INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS

DOI

https://doi.org/10.1002/int.20029

Collections

Department of Computer Engineering, Article

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Citation Formats

O. Bahar and A. Yazıcı, “Normalization and lossless join decomposition of similarity-based fuzzy relational databases,” INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, pp. 885–917, 2004, Accessed: 00, 2020. [Online]. Available: https://hdl.handle.net/11511/62697.