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title:
 
Pavelka-style fuzzy logic for attribute implications
publication:
 
JCIS-2006 Proceedings
part of series:
  Advances in Intelligent Systems Research
ISBN:
  978-90-78677-01-7
ISSN:
  1951-6851
DOI:
  doi:10.2991/jcis.2006.282 (how to use a DOI)
author(s):
 
Radim Belohlavek, Vilem Vychodil
corresponding author:
 
Radim Belohlavek
publication date:
 
October 2006
keywords:
 
attribute dependency, fuzzy logic, attribute implication, Armstrong axioms, graded completeness
abstract:
 
We present Pavelka-style fuzzy logic for reasoning about attribute implications, i.e. formulas $A\Rightarrow B$. Fuzzy attribute implications allow for two different interpretations, namely, in data tables with graded (fuzzy) attributes and in data tables over domains with similarity relations. The axioms of our logic are inspired by well-known Armstrong axioms but the logic allows us to infer partially true formulas from partially true formulas. We prove soundness and completeness of our logic in graded style, i.e. we prove that a degree to which an attribute implication $A\Rightarrow B$ semantically follows from a collection $T$ of partially true attribute implications equals a degree to which $A\Rightarrow B$ is provable from $T$.
copyright:
 
© Atlantis Press. This article is distributed under the terms of the Creative Commons Attribution License, which permits non-commercial use, distribution and reproduction in any medium, provided the original work is properly cited.
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