Abstract
Recently, ontologies are proposed for many purposes to assist decision making, such as representing terminology and categorizing information. Current ontology-based decision support systems mainly contain semantically rich decision rules. In order to ground the semantics, we formalize those rules by committing them to domain ontologies. Those semantically grounded decision rules can represent the semantics precisely, thus improve the functionalities of many available rule engines. We model and visualize the rules by means of a novel extension of ORM. These rules are further stored in an XML-based markup language, ORM + ML, which is a hybrid language of Rule-ML and ORM-ML. We demonstrate in the field of on-line customer management.
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Tang, Y., Spyns, P., Meersman, R. (2007). Towards Semantically Grounded Decision Rules Using ORM + . In: Paschke, A., Biletskiy, Y. (eds) Advances in Rule Interchange and Applications. RuleML 2007. Lecture Notes in Computer Science, vol 4824. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-75975-1_7
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DOI: https://doi.org/10.1007/978-3-540-75975-1_7
Publisher Name: Springer, Berlin, Heidelberg
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