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Parallel OWL Reasoning: Merge Classification

机译:并行OWL推理:合并分类

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Our research is motivated by the ubiquitous availability of multiprocessor computers and the observation that available Web Ontology Language (OWL) reasoners only make use of a single processor. This becomes rather frustrating for users working in ontology development, especially if their ontologies are complex and require long processing times using these OWL reasoners. We present a novel algorithm that uses a divide and conquer strategy for parallelizing OWL TBox classification, a key task in description logic reasoning. We discuss some interesting properties of our algorithm, e.g., its suitability for distributed reasoning, and present an empirical study using a set of benchmark ontologies, where a speedup of up to a factor of 4 has been observed when using 8 workers in parallel.
机译:我们的研究受到多处理器计算机无处不在的可用性的启发,并且观察到可用的Web本体语言(OWL)推理程序仅使用单个处理器。对于从事本体开发工作的用户而言,这尤其令人沮丧,尤其是当其本体复杂且需要使用这些OWL推理程序的处理时间较长时。我们提出了一种新颖的算法,该算法使用分而治之的策略来并行化OWL TBox分类,这是描述逻辑推理中的关键任务。我们讨论了该算法的一些有趣特性,例如其对分布式推理的适用性,并使用一组基准本体进行了实证研究,其中当并行使用8个工人时,观察到的加速高达4倍。

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