Elimination of semantic ambiguity in fuzzy relational models

M. Nakata
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引用次数: 3

Abstract

A generalized possibility-distribution-fuzzy-relational-model is proposed considering semantic ambiguity for values of membership attribute and ambiguity contained in values of membership attribute. Then the extended relational algebra is shown. In order to eliminate the semantic ambiguity, the concept of membership is introduced into each attribute. This clarifies the origin of membership attribute values. What the value of membership means depends on the property of attributes. In order to eliminate ambiguity contained in values of membership attribute those values are expressed by fuzzy values. This clarifies what relationships fuzzy data values have with their membership attribute values. Therefore there is no semantic ambiguity for the values of membership attributes and no ambiguity in the values of membership attributes in our extended relational model.
模糊关系模型中语义歧义的消除
考虑了隶属属性值的语义模糊性和隶属属性值中包含的模糊性,提出了一种广义的可能性-分布-模糊关系模型。然后给出了扩展关系代数。为了消除语义歧义,在每个属性中引入了隶属度的概念。这澄清了成员属性值的来源。成员值的含义取决于属性的属性。为了消除隶属属性值中所包含的模糊性,将隶属属性值表示为模糊值。这阐明了模糊数据值与其成员属性值之间的关系。因此,在我们的扩展关系模型中,成员属性的值不存在语义歧义,成员属性的值也不存在歧义。
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