From Horn-SRIQ to Datalog: A Data-Independent Transformation that Preserves Assertion Entailment

David CarralDavid Carral, Larry GonzálezLarry González, Patrick KoopmannPatrick Koopmann

David Carral, Larry González, Patrick Koopmann
From Horn-SRIQ to Datalog: A Data-Independent Transformation that Preserves Assertion Entailment
Proceedings of the 33rd Conference on Artificial Intelligence (AAAI 2019), January 2019

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KurzfassungAbstract
Ontology-based access to large data-sets has recently gained a lot of attention. To access data efficiently, one approach is to rewrite the ontology into Datalog, and then use powerful Datalog engines to compute implicit entailments. Existing rewriting techniques support Description Logics (DLs) from ELH to Horn-SHIQ. We go one step further and present one such data-independent rewriting technique for Horn-SRIQ, the extension of Horn-SHIQ that supports non-transitive, complex roles---an expressive feature prominently used in many real-world ontologies. We evaluated our rewriting technique on a large known corpus of ontologies. Our experiments show that the resulting rewritings are of moderate size and that the use our approach is more efficient than state-of-the-art DL reasoners when reasoning with data-intensive ontologies.
Projekt:Project: DIAMOND, HAEC B08, Cfaed
Forschungsgruppe:Research Group: AutomatentheorieAutomata Theory, Wissensbasierte SystemeKnowledge-Based Systems

@inproceedings{CGK2019,
  author    = {David Carral and Larry Gonz{\'{a}}lez and Patrick Koopmann},
  title     = {From Horn-SRIQ to Datalog: A Data-Independent Transformation that
               Preserves Assertion Entailment},
  booktitle = {Proceedings of the 33rd Conference on Artificial Intelligence
               (AAAI 2019)},
  year      = {2019},
  month     = {January}
}