2004 | OriginalPaper | Buchkapitel
Considering Semantic Ambiguity and Indistinguishability for Values of Membership Attribute in Possibility-Based Fuzzy Relational Models
verfasst von : Michinori Nakata
Erschienen in: Rough Sets and Current Trends in Computing
Verlag: Springer Berlin Heidelberg
Enthalten in: Professional Book Archive
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A possibility-based fuzzy relational model is proposed under considering semantic ambiguity and indistinguishability for values of membership attribute. In order to eliminate the semantic ambiguity, a membership attribute is attached to every attribute. This clarifies where each value of membership attributes comes from. What the values of membership attributes mean depends on the property of those attributes. In order to eliminate the indistinguishability for values of membership attribute, these values are expressed by possibility distributions on the interval [0,1]. This clarifies what effects an imprecise data value allowed for an attribute has on its value of membership attribute. Therefore, there is no semantic ambiguity and no indistinguishability for the values of membership attributes in the possibility-based fuzzy relational model.