EXTENDING RELATIONAL DATABASE MODEL FOR UNCERTAIN INFORMATION

Hoa Nguyen
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引用次数: 2

Abstract

In this paper, we propose a new probabilistic relational database model, denote by PRDB, as an extension of the classical relational database model where the uncertainty of relational attribute values and tuples are respectively represented by finite sets and probability intervals. A probabilistic interpretation of binary relations on finite sets is proposed for the computation of their probability measures. The combination strategies on probability intervals are employed to combine attribute values and compute uncertain membership degrees of tuples in a relation. The fundamental concepts of the classical relational database model are extended and generalized for PRDB. Then, the probabilistic relational algebraic operations are formally defined accordingly in PRDB. In addition, a set of the properties of the algebraic operations in this new model also are formulated and proven.
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扩展不确定信息的关系数据库模型
本文提出了一种新的概率关系数据库模型(PRDB),作为经典关系数据库模型的扩展,其中关系属性值和元组的不确定性分别用有限集合和概率区间表示。提出了有限集合上二元关系的概率解释,用于计算它们的概率测度。利用概率区间上的组合策略组合属性值,计算关系中元组的不确定隶属度。经典关系数据库模型的基本概念在PRDB中得到了扩展和推广。然后,在PRDB中对相应的概率关系代数运算进行形式化定义。此外,还给出了该模型中代数运算的一系列性质,并给出了证明。
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