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<a target="_blank" rel="noopener" href="https://fatcat.wiki/container/2w3awgokqne6te4nvlofavy5a4" style="color: black;">Lecture Notes in Computer Science</a>
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<span class="external-identifiers"> <a target="_blank" rel="external noopener noreferrer" href="https://doi.org/10.1007/978-3-642-15120-0_4">doi:10.1007/978-3-642-15120-0_4</a> <a target="_blank" rel="external noopener" href="https://fatcat.wiki/release/nsyydk4xffgaxkorllgy3hhn2a">fatcat:nsyydk4xffgaxkorllgy3hhn2a</a> </span>
more »... 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. Keywords: ontology matching, matching performance, parallel matching Recently, the development and maintenance of ontology mappings interconnecting different (multiple) related ontologies have gained importance, e.g., to integrate heterogeneous information sources (e.g.,  ), to merge ontologies  , or to support analysis such as the comparison of expression patterns  . Since the manual creation of such ontology mappings is time-consuming or even infeasible their semi-automatic generation called ontology matching [24, 9] has become an active research field especially for life science ontologies (e.g., [22, 4, 17, 26] ). Effective ontology matching, i.e. the computation of high quality mappings, typically entails the combined execution of several matchers to determine the similarity between ontology elements based on metadata or instance data (see [24, 9] ). For large Figure 3: Element-level matching on Name attribute 0.5 0.6 Acc: c 1 Name: c1.name
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