Abstract. Matching life science ontologies to determine ontology mappings has recently become an active field of research. The large size of existing ontologies and the application of complex match strategies for obtaining high quality mappings makes ontology matching a resource- and time-intensive process. To improve performance we investigate different approaches for parallel matching on multiple compute nodes. In particular, we consider inter-matcher and intramatcher parallelism as well as the parallel execution of element- and structurelevel matching. We implemented a distributed infrastructure for parallel ontology matching and evaluate different approaches for parallel matching of large life science ontologies in the field of anatomy and molecular biology
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