A Relational Database Model with Probability Intervals for Uncertain Set-Valued Attributes

Abstract

Although the conventional relational database model is very useful for modeling, designing and implementing large-scale systems, it is limited for expressing and dealing with uncertain and imprecise information. In this paper, we introduce a new relational database model whose relational attributes may take a set of values associated with a probability interval for representing and handling uncertain and imprecise information in practice. To build the new database model, we use three key methods: (1) Extended probabilistic values of set data types are proposed for representing uncertain set-valued attributes; (2) The probabilistic interpretations of binary relations on sets are defined for computing the uncertain degree of relations on set values of relational attributes; and (3) The combination strategies of probability intervals are employed for manipulating uncertain data relations. Then, fundamental concepts as schemas, probabilistic relations, probabilistic relational database, the selection operation and uncertain and imprecise information queries are defined coherently and consistently for the new model.

Keywords

• Probability Interval
• Uncertain Set-Valued Attributes
• Probabilistic Values
• Probabilistic Relations
• UIRDB model