Abstract
Information systems knowledge bases often include inference rules. The continuous growth of the facts in the recent information systems environments has caused the exponential increase of rule bases sizes. Therefore, rule bases management becomes more and more difficult. Such a task should be automated and based on the extraction of dependencies between rules in order to have a better insight on their correct execution order and to detect conflicts between them. In this paper, we describe a rules dependency extraction approach for Semantic Web Rule Language (SWRL) rules. Our approach insures the automatic extraction of a rule dependency graph based on the semantics of their components. We evaluated our work by applying it to two different ontologies from medical and network security domains. We have implemented a prototype of our approach and we integrated it in a plug-in for Potégé-Owl editor.
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Boujelben, A., Chaari, T., Amous, I. (2017). Towards Better SWRL Rules Dependency Extraction. In: Madureira, A., Abraham, A., Gamboa, D., Novais, P. (eds) Intelligent Systems Design and Applications. ISDA 2016. Advances in Intelligent Systems and Computing, vol 557. Springer, Cham. https://doi.org/10.1007/978-3-319-53480-0_77
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