Embracing Change by Abstraction Materialization Maintenance for Large ABoxes
Embracing Change by Abstraction Materialization Maintenance for Large ABoxes
Markus Brenner, Birte Glimm
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence
Main track. Pages 1767-1773.
https://doi.org/10.24963/ijcai.2018/244
Abstraction Refinement is a recently introduced technique which allows for reducing materialization of an ontology with a large ABox to materialization of a smaller (compressed) `abstraction' of this ontology. In this paper, we show how Abstraction Refinement can be adopted for incremental ABox materialization by combining it with the well-known DRed algorithm for materialization maintenance. Such a combination is non-trivial and to preserve soundness and completeness, already Horn ALCHI requires more complex abstractions. Nevertheless, we show that significant benefits can be obtained for synthetic and real-world ontologies.
Keywords:
Knowledge Representation and Reasoning: Description Logics and Ontologies
Knowledge Representation and Reasoning: Logics for Knowledge Representation