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General Information
    • ISSN: 2382-6185
    • Frequency: Quarterly (2015-2016); semiyearly (Since 2017)
    • DOI: 10.18178/IJKE
    • Editor-in-Chief: Prof. Chen-Huei Chou
    • Executive Editor: Ms. Nina Lee
    • Indexed by: Google Scholar, Crossref, ProQuest
    • E-mail: ijke@ejournal.net
Prof. Chen-Huei Chou
College of Charleston, SC, USA
It is my honor to be the editor-in-chief of IJKE. I will do my best to help develop this journal better.
IJKE 2018 Vol.4(1): 10-16 ISSN: 2382-6185
doi: 10.18178/ijke.2018.4.1.093

OntoJIT: Exploiting CLR Compiler Support for Performing Entailment Reasoning over Executable Ontologies

S. Baset and K. Stoffel
Abstract—Most recent efforts on bringing ontologies into mainstream programming languages were hindered by some fundamental issues; mainly the lack of expressiveness of programming languages compared to the declarative nature of ontological languages as well as the different assumptions on which reasoning in these languages is based on. In this paper we give the idea of adopting ontological programming approaches a second thought by proposing a prototype for a C# ontological knowledgebase system where ontologies are expressed directly in an executable form. We present our experience on bridging the semantic gab in general purpose programming languages and on exploiting metaprogramming and the dynamic compilation feature of modern compilers for performing certain entailment queries without the need for the bulky ontology classification step usually required in the case of conventional ontological tools.

Index Terms—Dynamic compilation, executable ontologies, metaprogramming, OntoJIT, OWL, semantic programming.

S. Baset and K. Stoffel are with the Information Management Institute of University of Neuchâtel, A.L.Breguet 2, CH-2000 Neuchâtel, Suisse (e-mail: sohaila.baset@unine.ch, kilian.stoffel@unine.ch).


Cite: S. Baset and K. Stoffel, "OntoJIT: Exploiting CLR Compiler Support for Performing Entailment Reasoning over Executable Ontologies," International Journal of Knowledge Engineering vol. 4, no. 1, pp. 10-16, 2018.

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