Data Management

Towards Scalability Issue in Ontology-Based Context-Aware Systems

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Executive Summary

Ontology is a promising tool to organize and represent context information. It arguably is superior to other context models in formality of semantics and the ability to deduce new facts. However, further usage of ontology-based systems is hindered by the slow reasoning speed of ontology engines and the monolithism of ontology knowledge bases. This paper proposes a fast and complete algorithm to extract subdatabases from the knowledge base for a given task. This algorithm is "Fast" because it does not require an OWL (Web Ontology Language) reasoning process when filtering existing OWL triples and when synchronizing newly-added triples.

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