Abstract
Knowledge management applications need to determine whether two or more knowledge representations encode the same knowledge. Solving this matching problem is hard because representations may encode the same content but differ substantially in form. Previous approaches to this problem have used either syntactic measure or semantic knowledge to determine the distance between two representations. The aim of this article is to define matching and merging of ontologies using conceptual graphs. The algorithms developed for matching and merging of m conceptual graphs are illustrated using health care domain ontologies. The mathematical aspects of matching and binding of m conceptual graphs with fitness are also discussed. Further with the help of transformations the matching process is improved to provide semantic matching.
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Ganapathy, G., Lourdusamy, R. (2013). Using Conceptual Graph Matching Methods to Semantically Mediate Ontologies. In: Ao, SI., Gelman, L. (eds) Electrical Engineering and Intelligent Systems. Lecture Notes in Electrical Engineering, vol 130. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-2317-1_18
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DOI: https://doi.org/10.1007/978-1-4614-2317-1_18
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