2015
DOI: 10.1016/j.ins.2014.09.059
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On minimal sets of graded attribute implications

Abstract: We explore the structure of non-redundant and minimal sets consisting of graded if-then rules. The rules serve as graded attribute implications in object-attribute incidence data and as similarity-based functional dependencies in a similarity-based generalization of the relational model of data. Based on our observations, we derive a polynomial-time algorithm which transforms a given finite set of rules into an equivalent one which has the least size in terms of the number of rules.

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Cited by 4 publications
(2 citation statements)
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“…In fact, for * being the globalization, (17) translates into (14). In [53], a criterion for minimality of a general set of FAIs for * being the globalization is described.…”
Section: Preliminariesmentioning
confidence: 99%
“…In fact, for * being the globalization, (17) translates into (14). In [53], a criterion for minimality of a general set of FAIs for * being the globalization is described.…”
Section: Preliminariesmentioning
confidence: 99%
“…Theory is called redundant whenever there is ⊂ such that ≡ ; otherwise is called non-redundant. Theory is called minimal [42] whenever for each such that ≡ , we have | | ≤ | |. One of the basic properties of non-redundant sets of graded attribute implications is the following: is…”
Section: Remarkmentioning
confidence: 99%