Abstract
Ontology evaluation has been recognized for a long time now as an important part of the ontology development lifecycle, and several methods, processes and metrics have been developed for that purpose. Nevertheless, vagueness is a quality dimension that has been neglected from most current approaches. Vagueness is a common human knowledge and linguistic phenomenon, typically manifested by terms and concepts that lack clear applicability conditions and boundaries such as high, expert, bad, near etc. As such, the existence of vague terminology in an ontology may hamper the latter’s quality, primarily in terms of shareability and meaning explicitness. With that in mind, in this short paper we argue for the need of including vagueness in the ontology evaluation activity and propose a set of metrics to be used towards that goal.
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Alexopoulos, P., Mylonas, P. (2014). Towards Vagueness-Oriented Quality Assessment of Ontologies. In: Likas, A., Blekas, K., Kalles, D. (eds) Artificial Intelligence: Methods and Applications. SETN 2014. Lecture Notes in Computer Science(), vol 8445. Springer, Cham. https://doi.org/10.1007/978-3-319-07064-3_38
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DOI: https://doi.org/10.1007/978-3-319-07064-3_38
Publisher Name: Springer, Cham
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