UCT CS Research Document Archive

Introducing Defeasibility into OWL Ontologies

Casini, Giovanni, Thomas Meyer, Kody Moodley, Ulrike Sattler and Ivan Varzinczak (2015) Introducing Defeasibility into OWL Ontologies. In Arenas, M, O Corcho, E Strohmaier, M d'Aquin, K Srinivas, P Groth, M Dumontier, J Heflin, K Thirunarayan and S Staab, Eds. Proceedings 14th International Semantic Web Conference (ISWC), pages 409-426, Bethlehem, Pennsylvania, USA.

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In recent years, various approaches have been developed for repre- senting and reasoning with exceptions in OWL. The price one pays for such ca- pabilities, in terms of practical performance, is an important factor that is yet to be quantified comprehensively. A major barrier is the lack of naturally oc- curring ontologies with defeasible features - the ideal candidates for evaluation. Such data is unavailable due to absence of tool support for representing defea- sible features. In the past, defeasible reasoning implementations have favoured automated generation of defeasible ontologies. While this suffices as a prelimi- nary approach, we posit that a method somewhere in between these two would yield more meaningful results. In this work, we describe a systematic approach to modify real-world OWL ontologies to include defeasible features, and we ap- ply this to the Manchester OWL Repository to generate defeasible ontologies for evaluating our reasoner DIP (Defeasible-Inference Platform). The results of this evaluation are provided together with some insights into where the performance bottle-necks lie for this kind of reasoning. We found that reasoning was feasible on the whole, with surprisingly few bottle-necks in our evaluation.

EPrint Type:Conference Paper
Subjects:I Computing Methodologies: I.2 ARTIFICIAL INTELLIGENCE
ID Code:1068
Deposited By:Meyer, Thomas
Deposited On:11 March 2016
Alternative Locations:http://iswc2015.semanticweb.org/sites/iswc2015.semanticweb.org/files/93670351.pdf, http://link.springer.com/chapter/10.1007%2F978-3-319-25010-6_27#page-1