A Probabilistic Relational Database Model with Fuzzy Attribute Values

Abstract

Although there have been many probabilistic or fuzzy relational database models proposed for representing and handling uncertain or imprecise information of objects in real-world applications, models combining the relevance and strength of both probability theory and fuzzy set theory appear sporadic. In this paper, we propose a new probabilistic and fuzzy relational database model where the uncertainty of a relational tuple is represented by a probability interval and the imprecision of an attribute value is represented by a fuzzy set. The mass assignment framework is employed to deal with the challenge of integration and computation of both probabilities and fuzzy sets in the same model. The fundamental concepts of the classical relational database model are extended and generalized in this new model. Then the syntax and semantics of the selection operation are formally defined accordingly.