Authors:
Sebastian Wandelt
and
Ralf Moeller
Affiliation:
Hamburg University of Technology, Germany
Keyword(s):
Description Logics, Reasoning, Scalability, Partitioning.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Collaboration and e-Services
;
Data Engineering
;
e-Business
;
Enterprise Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Engineering and Ontology Development
;
Knowledge Representation
;
Knowledge-Based Systems
;
Ontologies and the Semantic Web
;
Ontology Engineering
;
Semantic Web
;
Soft Computing
;
Symbolic Systems
Abstract:
In the last years, the vision of the Semantic Web fostered the interest in reasoning over ever larger sets of assertional statements in ontologies. It is easily conjectured that, soon, real-world ontologies will not fit into main memory anymore. If this was the case, state-of-the-art description logic reasoning systems cannot deal with these ontologies any longer, since they rely on in-memory structures.
We propose a way to overcome this problem by reducing instance checking for an individual in an ontology to a (usually small) relevant subsets of assertional axioms. These subsets are computed based on a partitioning-criteria. We propose a way to preserve the partitions while updating an ontology and thus enable stream like reasoning for description logic ontologies. We think that this technique can support description logic systems to deal with the upcoming large amounts of fluctuant assertional data.