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Model Based Deduction for Database Schema Reasoning

MPG-Autoren
http://pubman.mpdl.mpg.de/cone/persons/resource/persons44088

Baumgartner,  Peter
Programming Logics, MPI for Informatics, Max Planck Society;

Frühwirth,  Thom
Max Planck Society;

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Zitation

Baumgartner, P., Furbach, U., Gross-Hardt, M., & Kleemann, T. (2004). Model Based Deduction for Database Schema Reasoning. In KI 2004: Advances in Artificial Intelligence: 27th Annual German Conference on AI, KI 2004 (pp. 168-182). Berlin, Germany: Springer.


Zitierlink: http://hdl.handle.net/11858/00-001M-0000-000F-2963-4
Zusammenfassung
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.