A Probabilistic Data Model and Its Semantics

Abstract

As database systems are increasingly being used in advanced applications, it is becoming common that data in these applications contain some elements of uncertainty. These arise from many factors, such as measurement errors and cognitive errors. As such, many researchers have focused on defining comprehensive uncertainty data models of uncertainty database systems. However, existing uncertainty data models do not adequately support some applications. Moreover, very few works address uncertainty tuple calculus. In this paper we advocate a probabilistic data model for representing uncertain information. In particular, we establish a probabilistic tuple calculus language and its semantics to meet the corresponding probabilistic relational algebra.