Abstract
This study compares the expressive power of Resource Data Framework (RDF) and Inductive Logic Programing (ILP). While RDF and RDF Schema do not possess any rule language, ILP is a logic programing language that is fit for inferring facts. The research aims to identify and acknowledge the differences between RDF and ILP in terms of how much expressive power they hold within themselves and how efficient they infer knowledge when employed in ontologies. The paper represents ongoing work to compare RDF and ILP.
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Acknowledgments
The research presented here has been carried out within the Dare2Del project under the DFG priority program Intentional Forgetting (SPP 1921). Dare2Del is a joint project of Cognitive Systems, University of Bamberg and the Chair for Work and Organisational Psychology, University of Erlangen.
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Nandini, D. (2022). A Comparison of Resource Data Framework and Inductive Logic Programing for Ontology Development. In: Fujita, H., Fournier-Viger, P., Ali, M., Wang, Y. (eds) Advances and Trends in Artificial Intelligence. Theory and Practices in Artificial Intelligence. IEA/AIE 2022. Lecture Notes in Computer Science(), vol 13343. Springer, Cham. https://doi.org/10.1007/978-3-031-08530-7_73
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DOI: https://doi.org/10.1007/978-3-031-08530-7_73
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