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.

📈 Trend Setter — Ontology Learning
🧭 Keyword Pioneer — ontology engineering
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Deep Learning, Healthcare & Medicine, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Robotics, Security & Privacy