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Towards Evaluating an Ontology-Based Data Matching Strategy for Retrieval and Recommendation of Security Annotations for Business Process Models

Abstract : In the Trusted Architecture for Securely Shared Services (TAS3) EC FP7 project we have developed a method to provide semantic support to the process modeler during the design of secure business process models. Its supporting tool, called Knowledge Annotator (KA), is using ontology-based data matching algorithms and strategy in order to infer the recommendations the best fitted to the user design intent, from a dedicated knowledge base. The paper illustrates how the strategy is used to perform the similarity (matching) check in order to retrieve the best design recommendation. We select the security and privacy domain for trust policy specification for the concept illustration. Finally, the paper discusses the evaluation of the results using the Ontology-based Data Matching Framework evaluation benchmark.
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Ioana Ciuciu, Yan Tang, Robert Meersman. Towards Evaluating an Ontology-Based Data Matching Strategy for Retrieval and Recommendation of Security Annotations for Business Process Models. 1st International Symposium on Data-Driven Process Discovery and Analysis (SIMPDA), Jun 2011, Campione d’Italia, Italy. pp.103-119, ⟨10.1007/978-3-642-34044-4_6⟩. ⟨hal-01515543⟩

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