Abstract
Existing efforts on ontology mapping, alignment and merging vary from methodological and theoretical frameworks, to methods and tools that support the semi-automatic coordination of ontologies. However, only latest research efforts “touch” on the mapping /merging of ontologies using the whole breadth of available knowledge. Addressing this issue, the work presented in this paper is based on the HCONE-merge approach that makes use of the intended informal interpretations of concepts by mapping them to WordNet senses using lexical semantic indexing (LSI). Our aim is to explore the level of human involvement required for mapping concepts of the source ontologies to their intended interpretations. We propose a series of methods for ontology mapping/merging with varying degrees of human involvement and evaluate them experimentally. We conclude that, although an effective fully automated process is not attainable, we can reach a point where the process of ontology mapping/merging can be carried out efficiently with minimum human involvement.
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Kotis, K., Vouros, G.A., Stergiou, K. (2004). Capturing Semantics Towards Automatic Coordination of Domain Ontologies. In: Bussler, C., Fensel, D. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2004. Lecture Notes in Computer Science(), vol 3192. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30106-6_3
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DOI: https://doi.org/10.1007/978-3-540-30106-6_3
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