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An Implementation for Fuzzy Deductive Relational Databases

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Recent Issues on Fuzzy Databases

Part of the book series: Studies in Fuzziness and Soft Computing ((STUDFUZZ,volume 53))

Abstract

This chapter shows how to integrate the representation of deductive rules and fuzzy information stored in a relational DBMS to build a module that can obtain new data from data stored in tables. The deductions can be applied to classical (or precise) data, imprecise data or both of them, so it is necessary to provide a mechanism to find the tuples in the database satisfying a rule, i.e. a mechanism to calculate the precision degree of the answer by means of the combination of the precision degrees of every value into an unified measure. Keywords, relational databases extension, fuzzy deduction, inference.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Artificial IntelligenceUniversity of Granada, Granada, Spain

    Ignacio Blanco, Juan C. Cubero, Olga Pons & Amparo Vila

Authors
  1. Ignacio Blanco
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  2. Juan C. Cubero
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  3. Olga Pons
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  4. Amparo Vila
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Editor information

Editors and Affiliations

  1. Istituto per le Tecnologie Informatiche Multimediali, Consiglio Nazionale delle Ricerche, Via Ampere 56, 20133, Milano, Italy

    Gloria Bordogna  & Gabriella Pasi  & 

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© 2000 Springer-Verlag Berlin Heidelberg

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Blanco, I., Cubero, J.C., Pons, O., Vila, A. (2000). An Implementation for Fuzzy Deductive Relational Databases. In: Bordogna, G., Pasi, G. (eds) Recent Issues on Fuzzy Databases. Studies in Fuzziness and Soft Computing, vol 53. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1845-1_9

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  • DOI: https://doi.org/10.1007/978-3-7908-1845-1_9

  • Publisher Name: Physica, Heidelberg

  • Print ISBN: 978-3-7908-2476-6

  • Online ISBN: 978-3-7908-1845-1

  • eBook Packages: Springer Book Archive

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