2004
DOI: 10.1016/j.fss.2003.10.021
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Similarities between powersets of terms

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Cited by 11 publications
(5 citation statements)
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“…A first step towards similarities between powersets of terms was done in [8] involving fuzzy relations for crisp powersets of terms. Using proof techniques presented in this paper, a range of interesting powerset functors can be further investigated.…”
Section: Discussionmentioning
confidence: 99%
“…A first step towards similarities between powersets of terms was done in [8] involving fuzzy relations for crisp powersets of terms. Using proof techniques presented in this paper, a range of interesting powerset functors can be further investigated.…”
Section: Discussionmentioning
confidence: 99%
“…The principal idea of the categorical approach was an observation that classical powerset objects constitute the so-called algebraic theory (or monad), introduced by E. G. M a n e s [19]. Roughly speaking, there exists an algebraic theory (in clone form) P = (P, η, ♦) in the category Set, where P(X) = 2 X (see [2]), such that the operator f → P : P(X) → P(Y ) induced from P by setting f → P = (η B • f )♦1 P(X) is the same as f → . Similarly can be derived the powerset operator f ← P .…”
Section: Jiří Močkořmentioning
confidence: 99%
“…Similarly can be derived the powerset operator f ← P . In this sense, an algebraic theory P generates the traditional powerset theory [2]. In the same manner as in the case of an algebraic theory P = (P, η, ♦), which generates powerset operators in the category Set, we can formally proceed in defining algebraic theory Z = (Z, μ, ) which defines powerset operators for Q-valued fuzzy sets, where Q is an appropriate lattice.…”
Section: Jiří Močkořmentioning
confidence: 99%
“…For RC i in RC RC Store GC max GCmax = max {ConceptSim (RCi, GCj), ConceptSim (RCi, GC 'j)} j RC i is the number i concept name term set from requested product empirical knowledge concepts (i.e., RC i = {RC 1 , RC 2 , ... , RC i }). Attribute Name Set Matching based on Multi-experts: This step involves executing the attribute name set matching based on multi-experts by employing the Power Set method [24,25]. Figure 23 illustrates the algorithm procedure.…”
Section: Attribute Name Set Matching Of Practical Knowledge Itemmentioning
confidence: 99%