Extended Relational Database Model for Interval Probability Set-Valued Attributes

In this paper, we introduce a new probabilistic relational database model as an extension of the classical relational database model for interval probability set-valued attributes to represent and handle uncertain and imprecise information in practice. To develop the new model, we use extended probabilistic values for representing interval probability set-valued relational attributes and the probabilistic interpretation of binary relations on sets for computing uncertain degree of functional dependencies, keys and relations on attribute values, and propose the new combination strategies of extended probabilistic values for building probabilistic relational algebraic operations. A set of the properties of the basic probabilistic relational algebraic operations is also formulated and proven