Title :
Generalizing possibility-distribution-fuzzy-relational-models
Author :
Nakata, Michinori
Author_Institution :
Dept. of Inf. Sci., Chiba-Keizai Coll., Japan
Abstract :
A generalized possibility-distribution fuzzy-relational model is proposed, considering semantic ambiguity for membership attribute values and the ambiguity contained in them. Then, an extended relational algebra is shown. In order to eliminate the semantic ambiguity, a membership attribute is attached to each attribute. This clarifies the origin of membership attribute values. What a membership attribute value means depends on the properties of the attribute. In order to eliminate the ambiguity contained in membership attribute values, those values are expressed by possibility distributions. This clarifies what effects an imprecise attribute value has on its membership attribute value. Therefore, there is no semantic ambiguity for the membership attribute values, and no ambiguity in them in the extended relational model
Keywords :
database theory; fuzzy set theory; generalisation (artificial intelligence); possibility theory; relational algebra; uncertainty handling; attribute properties; extended relational algebra; fuzzy-relational model; imprecise attribute value; membership attribute values; model generalization; possibility distribution; semantic ambiguity; Algebra; Cities and towns; Databases; Educational institutions; Fuzzy set theory; Fuzzy sets; Information science; Intelligent systems; Marine vehicles; Query processing;
Conference_Titel :
Knowledge-Based Intelligent Information Engineering Systems, 1999. Third International Conference
Conference_Location :
Adelaide, SA
Print_ISBN :
0-7803-5578-4
DOI :
10.1109/KES.1999.820238
