Reference : Introducing Defeasibility into OWL Ontologies
Scientific congresses, symposiums and conference proceedings : Paper published in a book
Engineering, computing & technology : Computer science
Introducing Defeasibility into OWL Ontologies
Casini, Giovanni mailto [University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Computer Science and Communications Research Unit (CSC) >]
Meyer, Thomas mailto [University of Cape Town > Computer Science]
Moodley, Kody mailto [University of Kwazulu-Natal > Computer Science]
Sattler, Uli mailto [University of manchester > Computer Science]
Varzinczak, Ivan mailto [Universidade Federal Do Rio de Janeiro > Computer Science]
14th International Semantic Web Conference. Bethlehem, PA, USA, October 11–15, 2015 Proceedings, Part II
Arenas, Marcelo
Corcho, Oscar
Simperl, Elena
Strohmaier, Markus
d’Aquin, Mathieu
Srinivas, Kavitha
Groth, Paul
Dumontier, Michel
Heflin, Jeff
Thirunarayan, Krishnaprasad
Staab, Steffen
Lecture Notes in Computer Science 9367
14th International Semantic Web Conference (ISWC)
from 11-10-2015 to 15-10-2015
[en] typicality ; nonmonotonic reasoning ; description logics
[en] In recent years, various approaches have been developed for
representing and reasoning with exceptions in OWL. The price one pays
for such capabilities, in terms of practical performance, is an important
factor that is yet to be quantified comprehensively. A major barrier is
the lack of naturally occurring ontologies with defeasible features - the
ideal candidates for evaluation. Such data is unavailable due to absence
of tool support for representing defeasible features. In the past, defeasible
reasoning implementations have favoured automated generation of defeasible
ontologies. While this suffices as a preliminary 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 apply
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.
FnR ; FNR9181001 > Giovanni Casini > > Subjective and Objective Uncertainty in Description Logics > 01/07/2015 > 30/06/2017 > 2014

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