Precision and Recall for Ontology Enrichment

Ontology enrichment algorithms propose new concepts to given concepts in a domain specific ontology. The paper is dedicated to the quality of ontology enrichment algorithms in terms of precision and recall. We remain open for the proposition of several new concepts to a given one instead of exactly one to a given one. Our first contribution is the generalization of known quality measures concerning recall for robust enrichment algorithms. In order to achieve independence from user evaluations and only rely on ontologies, text corpora and the output of the algorithms, there will be no appropriate explanation of precision in automatic evaluation but hints on precision. Our second contribution is an explanation of these hints on precision in corpus-based ontology enrichment. Finally we show, which measures allow a straightforward computation.

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