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Matches in ScholarlyData for { ?s ?p The aim of this paper is to benchmark various semantic repositories to evaluate their deployment in a commercial image retrieval and browsing technology. We adopt a two-phase approach for evaluating the target semantic repositories: analytical parameters such as query/reasoning language and expected minimum level of reasoning support are used to select the pool of the target repositories, and practical parameters such as load and query response times are used to select the best match to application requirements. In addition to utilising a widely accepted benchmark for OWL repositories (UOBM), we also use a real-life dataset from the target application, which provides us with the opportunity of consolidating our findings. A distinctive advantage of this benchmarking exercise is that the essential requirements for the target system such as the semantic expressivity and data scalability are clearly defined, which allows us to claim contribution to the benchmarking methodology for this class of applications.. }

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