E-Document Standards as Background Knowledge in Context-Based Ontology Matching

Abstract

Ontology matching is the process of finding correspondence between heterogeneous ontologies and consequently support semantic interoperability between different information systems. Using contextual information relative to the ontologies being matched is referred to as context-based ontology matching and is considered one promising direction of improving the matching performance. This PhD investigates how such contextual information, often residing in disparate sources and represented by different formats, can be optimally represented to ontology matching systems and how these systems best can employ this context to produce accurate and correct correspondences. Currently we are investigating how the international e-Document standard Universal Business Language from the transport logistics domain can provide useful context when matching domain ontologies for this particular domain. Early evaluation tests and analysis of the results suggest that the current version of the Universal Business Language ontology does not impact on the matching results and that further reconfiguration and enhancements are needed.