Abstract
In this study we explore if considering the domain similarity between concepts to be matched can contribute filter out false positive relations. This is particularly relevant in areas where the “universe of discourse” encompasses several diverse domains, such as cultural heritage. Our approach is based on an algorithm that employs the lexical resource WordNet Domains to filter out relations where the two concepts to be matched are associated with different domains. We evaluate our approach in an experiment involving Bibframe and Schema.org, two ontologies of complementary nature. The results from the evaluation show that the use of such a domain filter indeed can have a positive effect on reducing false positives while retaining true ones.
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Available at https://github.com/audunve/WordNetDomainsFilter.
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Vennesland, A., Aalberg, T. (2018). False-Positive Reduction in Ontology Matching Based on Concepts’ Domain Similarity. In: Méndez, E., Crestani, F., Ribeiro, C., David, G., Lopes, J. (eds) Digital Libraries for Open Knowledge. TPDL 2018. Lecture Notes in Computer Science(), vol 11057. Springer, Cham. https://doi.org/10.1007/978-3-030-00066-0_37
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