Detecting hidden errors in an ontology using contextual knowledge

作者：Teymourlouie Mehdi; Zaeri Ahmad; Nematbakhsh Mohammadali^*; Thimm Matthias; Staab Steffen

来源：Expert Systems with Applications, 2018, 95: 312-323.

DOI：10.1016/j.eswa.2017.11.034

• Ontology debugging
• Hidden modeling errors
• Contextual knowledge
• Incoherency
• Inconsistency

Due to modeling errors in designing ontologies, an ontology may carry incorrect information. Ontology debugging can be helpful in detecting errors in ontologies that are increasing in size and expressiveness day by day. While current ontology debugging methods can detect logical errors (incoherences and inconsistencies), they are incapable of detecting hidden modeling errors in coherent and consistent ontologies. From the logical perspective, there are no errors in such ontologies, but this study shows some modeling errors may not break the coherency of the ontology by not participating in any contradiction. In this paper, contextual knowledge is exploited to detect such hidden errors. Our experiments show that adding general ontologies like DBpedia as contextual knowledge in the ontology debugging process results in detecting contradictions in ontologies that are coherent.

• 出版日期2018-4-1