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Determining the size of an ontology that is automatically learned from texts is an open issue. In this paper, we study the similarity between ontology concepts at different levels of a taxonomy, quantifying in a natural manner the quality of the ontology attained. Our approach is integrated in a method for language-neutral learning of ontologies from texts, which relies on conditional independence tests over thematic topics that are discovered using LDA.
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