Abstract
The paper proposes an ontology alignment framework with two core features: the use of background knowledge and the ability to handle imprecision in the matching process and the resulting concept alignments. The procedure is based on the use of a generic reference vocabulary, which is used to define an explicit semantic space for the ontologies to be matched. General-purpose background knowledge sources based on Wikipedia, such as Yago, appear to be appropriate choices of reference vocabularies. The outcome of the procedure is a combined fuzzy knowledge body which captures what is common in two source ontologies. The proposed approach allows to discover cross-concept relations of the kind many-to-many. An important application of the method is found in the field of cross-lingual ontology matching.
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Todorov, K., Hudelot, C., Geibel, P. (2014). Fuzzy and Cross-Lingual Ontology Matching Mediated by Background Knowledge. In: Bobillo, F., et al. Uncertainty Reasoning for the Semantic Web III. URSW URSW URSW 2012 2011 2013. Lecture Notes in Computer Science(), vol 8816. Springer, Cham. https://doi.org/10.1007/978-3-319-13413-0_8
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