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Contribution Details

Type Conference or Workshop Paper
Scope Discipline-based scholarship
Published in Proceedings No
Title Semantic Process Retrieval with iSPARQL
Organization Unit
  • Christoph Kiefer
  • Abraham Bernstein
  • Hong Joo Lee
  • Mark Klein
  • Markus Stocker
Item Subtype Original Work
Refereed Yes
Status Published in final form
Event Title Proceedings of the 4th European Semantic Web Conference (ESWC '07)
Publisher Springer
Abstract Text The vision of semantic business processes is to enable the integration and inter-operability of business processes across organizational boundaries. Since different organizations model their processes differently, the discovery and retrieval of similar smantic business processes is necessary in order to foster inter-organi ational collaborations. This paper presents our approach of using iSPARQL � our imprecise query engine based on SPARQL � to query the OWL MIT Process Handbook � a large collection of over 5000 semantic business processes. We particularly show how easy it is to use iSPARQL to perform the presented process retrieval task. Furthermore, since choosing the best performing similarity strategy is a non-trivial, data-, and context-dependent task, we evaluate the performance of three simple and two human-engineered similarity strategies. In addition, we conduct machine learning experiments to learn similarity measures showing that complementary information contained in the different notions of similarity strategies provide a very high retrieval accuracy. Our preliminary results indicate that iSPARQL is indeed useful for extending the reach of queries and that it, therefore, is an enabler for inter- and intra-organizational collaborations.
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