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

David Carral, Larry González, Patrick Koopmann
2019 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
To access data efficiently, one approach is to rewrite the ontology into Datalog, and then use powerful Datalog engines to compute implicit entailments.  ...  We go one step further and present one such data-independent rewriting technique for Horn-SRIQ⊓, the extension of Horn-SHIQ that supports role chain axioms, an expressive feature prominently used in many  ...  Acknowledgements We thank Irina Dragoste for assisting us with the execution of the experiments, for which we used the servers from the Centre for Information Services and High Performance Computing (ZIH  ... 
doi:10.1609/aaai.v33i01.33012736 fatcat:7ozaadq5rzfthn56apkgwwjqya

Tractable approximate deduction for OWL

Jeff Z. Pan, Yuan Ren, Yuting Zhao
2016 Artificial Intelligence  
Evaluation on ontologies from benchmarks and real-world use cases shows that our approach can do reasoning on complex ontologies efficiently with a high recall. .  ...  In this paper, we present a tractable approximate reasoning framework for OWL 2 that improves efficiency and guarantees soundness.  ...  Thus all RIs in SI are independent to GCIs and ABox assertions. So for any RI β, we have β ∈ SI iff β ∈ ST . Similarly, because we have A ∈ T for all A ∈ CN T , we also have A ∈ ST and ⊥ A ∈ ST .  ... 
doi:10.1016/j.artint.2015.10.004 fatcat:fwysqcak3zhhthbglnd2bt4xze