Semantic Process Retrieval with iSPARQL
From semanticweb.org
A paper written by Hong Joo Lee, Christoph Kiefer, Mark Klein, Abraham Bernstein and Markus Stocker. It was presented at the ESWC2007. It is about iSPARQL, MIT Process Handbook, retrieval task and similarity measures
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[edit] Abstract
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 semantic business processes is necessary in order to foster inter-organizational collaborations. This paper presents our approach of using iSPARQL - our imprecise query engine based on SPARQL - to query the OWLized MIT Process Handbook - a large collection of over 5000 semantic business processes. We particularly show how it 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 complimentary 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.
This data has been imported from the ESWC2007 RDF
