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Content Provider | IEEE Xplore Digital Library |
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Author | Batet, M. Sanchez, D. |
Copyright Year | 2014 |
Description | Author affiliation: Dept. of Comput. Eng. & Math., Univ. Rovira i Virgili, Tarragona, Spain (Batet, M.; Sanchez, D.) |
Abstract | In recent years, ontologies have experienced an enormous development due to their importance in knowledge-based systems. Because of the discrepancies that may appear during the modeling of ontologies, and due to the availability of ontologies covering overlapping domains, ontology evaluation is crucial in order to select the most appropriate ontology for a specific application. Many ontology evaluation mechanisms available in the literature assess the quality of ontologies according to their structural features. Even though, most of them propose ad-hoc scores aggregating different features, which lacks semantic and mathematical coherence. In this paper, we present an intuitive measure for ontology evaluation that quantifies the semantic dispersion of the ontology, which is both mathematically and semantically coherent. Our proposal is inspired in the standard notion of numerical dispersion of a sample and on a recent empirical study showing which ontological features can better predict the accuracy of ontologies. Our experiments, performed over a set of widely used ontologies, suggest that our measure positively correlates with such features, while offering a more coherent ontology evaluation score. |
Starting Page | 138 |
Ending Page | 145 |
File Size | 810882 |
Page Count | 8 |
File Format | |
ISBN | 9781479965724 |
ISSN | 10823409 |
DOI | 10.1109/ICTAI.2014.30 |
Language | English |
Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Publisher Date | 2014-11-10 |
Publisher Place | Cyprus |
Access Restriction | Subscribed |
Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subject Keyword | Ontologies Semantics Dispersion Accuracy Taxonomy Standards Numerical models dispersion Knowledge representation ontology evaluation semantics |
Content Type | Text |
Resource Type | Article |
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