Model based deduction for database schema reasoning. (English) Zbl 1132.68359

Biundo, Susanne (ed.) et al., KI 2004: Advances in artificial intelligence. 27th annual German conference in AI, KI 2004, Ulm, Germany, September 20–24, 2004, Proceedings. Berlin: Springer (ISBN 978-3-540-23166-0/pbk). Lecture Notes in Computer Science 3238. Lecture Notes in Artificial Intelligence, 168-182 (2004).
Summary: We aim to demonstrate that automated deduction techniques, in particular those following the model computation paradigm, are very well suited for database schema/query reasoning. Specifically, we present an approach to compute completed paths for database or XPath queries. The database schema and a query are transformed to disjunctive logic programs with default negation, using a description logic as an intermediate language. Our underlying deduction system, KRHyper, then detects if a query is satisfiable or not. In case of a satisfiable query, all completed paths – those that fulfill all given constraints – are returned as part of the computed models.
The purpose of computing completed paths is to reduce the workload on a query processor. Without the path completion, a usual XPath query processor would search the whole database for solutions to the query, which need not be the case when using completed paths instead.
We understand this paper as a first step, that covers a basic schema/query reasoning task by model-based deduction. Due to the underlying expressive logic formalism we expect our approach to easily adapt to more sophisticated problem settings, like type hierarchies as they evolve within the XML world.
For the entire collection see [Zbl 1131.68004].


68P15 Database theory
68T05 Learning and adaptive systems in artificial intelligence
68T15 Theorem proving (deduction, resolution, etc.) (MSC2010)


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