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Probabilistic Object Bases

By Thomas Eiter, James Lu, Thomas Lukasiewicz and V.S. Subrahmanian

Abstract

There are many applications where an object oriented data model is a good way of representing and querying data. However, current object database systems are unable to handle the case of objects whose attributes are uncertain. In this paper, extending previous pioneering work by Kornatzky and Shimony, we develop an extension of the relational algebra to the case of object bases with uncertainty. We propose concepts of consistency for such object bases, together with an NP-completeness result, and classes of probabilistic object bases for which consistency is polynomially checkable. In addition, as certain operations involve conjunctions and disjunctions of events, and as the probability of conjunctive and disjunctive events depends both on the probabilities of the primitive events involved as well as on what is known (if anything) about the relationship between the events, we show how all our algebraic operations may be performed under arbitrary probabilistic conjunction and disjunction strategies. We also develop a host of equivalence results in our algebra, which may be used as rewrite rules for query optimization. Last but not least, we have developed a prototype probabilistic object base server using the VisiBroker ORB on top of ObjectStore. We describe experiments to assess the efficiency of different possible rewrite rules. (Also cross-referenced as UMIACS-TR-99-77

Year: 1999
OAI identifier: oai:drum.lib.umd.edu:1903/1049
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