An Implementation for Fuzzy Deductive Relational Databases

  • Ignacio Blanco
  • Juan C. Cubero
  • Olga Pons
  • Amparo Vila
Part of the Studies in Fuzziness and Soft Computing book series (STUDFUZZ, volume 53)


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.


Logical Rule Possibility Distribution Linguistic Label Extensional Table Underlying Domain 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Ignacio Blanco
    • 1
  • Juan C. Cubero
    • 1
  • Olga Pons
    • 1
  • Amparo Vila
    • 1
  1. 1.Department of Computer Science and Artificial IntelligenceUniversity of GranadaGranadaSpain

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