Patterns used to identify relations in corpus using formal concept analysis

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Abstract

In this paper we present an approach for the automatic identification of relations in ontologies of restricted domain. We use the evidence found in a corpus associated to the same domain of the ontology for determining the validity of the ontological relations. Our approach employs formal concept analysis, a method used for the analysis of data, but in this case used for relations discovery in a corpus of restricted domain. The approach uses two variants for filling the incidence matrix that this method employs. The formal concepts are used for evaluating the ontological relations of two ontologies. The performance obtained was about 96 for taxonomic relations and 100% for non-taxonomic relations, in the first ontology. In the second it was about 92% for taxonomic relations and 98% for non-taxonomic relations.

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Tovar, M., Pinto, D., Montes, A., Serna, G., & Vilariño, D. (2015). Patterns used to identify relations in corpus using formal concept analysis. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9116, pp. 236–245). Springer Verlag. https://doi.org/10.1007/978-3-319-19264-2_23

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