2018
IJCAI
IJCAI 2018
Embracing Change by Abstraction Materialization Maintenance for Large ABoxes
Abstract
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.
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Trend Setter
— Ontology Learning
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Keyword Pioneer
— ontology engineering
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics, Security & Privacy