Abstract
The generalized possibility-based fuzzy relational model we propose frees possibility-based fuzzy relational models from the semantic ambiguity and the indistinguishability of membership attribute values. We demonstrate extended relational algebra in this data model. To prevent the semantic ambiguity, a membership attribute is attached to every attribute. This clarifies where each membership attribute value comes from. What each membership attribute value means depends on the property of that attribute. To prevent the indistinguishability of membership attribute values, the value is expressed in a possibility distribution in interval [0,1]. This clarifies what effects the imprecise data value allowed for an attribute has on the membership attribute value. No semantic ambiguity and no indistinguishability of membership attribute values therefore exists in the generalized possibility-based fuzzy relational model.
Publisher
Fuji Technology Press Ltd.
Subject
Artificial Intelligence,Computer Vision and Pattern Recognition,Human-Computer Interaction
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