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Complexity Boundaries for Horn Description Logics




Published: 2007

Buchtitel: Proceedings of the 22nd AAAI Conference on Artficial Intelligence
Seiten: 452--457
Verlag: AAAI Press
Erscheinungsort: Vancouver, British Columbia, Canada
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Kurzfassung
Horn description logics (Horn-DLs) have recently started to attract attention due to the fact that their (worst-case) data complexities are in general lower than their overall (i.e. combined) complexities, which makes them attractive for reasoning with large ABoxes. However, the natural question whether Horn-DLs also provide advantages for TBox reasoning has hardly been addressed so far. In this paper, we therefore provide a thorough and comprehensive analysis of the combined complexities of Horn-DLs. While the combined complexity for many Horn-DLs turns out to be the same as for their non-Horn counterparts, we identify subboolean DLs where Hornness simplifies reasoning.

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Forschungsgebiet
Komplexitätstheorie, Theoretische Informatik, Logik