A Novel Combination of Reasoners for Ontology Classification

Changlong Wang, Zhiyong Feng
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引用次数: 5

Abstract

Large scale ontology applications require efficient reasoning services, of which ontology classification is the fundamental reasoning task. The special EL reasoners are efficient, but they can not classify ontologies with axioms outside the OWL 2 EL profile. The general-purpose OWL 2 reasoners for expressive Description Logics are less efficient when classifying the OWL 2 EL ontologies. In this work, we propose a novel technique that combines an OWL 2 reasoner with an EL reasoner for classification of ontologies expressed in DL SROIQ. We develop an efficient task decomposition algorithm for identifying the minimal non-EL module that is assigned to the OWL 2 reasoner, and the bulk of the workload is assigned to the EL reasoner. Furthermore, this paper reports on the implementation of our approach in the ComR system which integrates the two types of reasoners in a black-box manner. The experimental results show that our method leads to a reasonable task assignment and can offer a substantial speed up (over 50%) in ontology classification.
一种新的本体分类推理器组合
大规模的本体应用需要高效的推理服务,其中本体分类是最基本的推理任务。特殊的EL推理器是有效的,但它们不能对owl2 EL profile之外的公理本体进行分类。用于表达描述逻辑的通用owl2推理器在对owl2 EL本体进行分类时效率较低。在这项工作中,我们提出了一种结合OWL 2推理器和EL推理器的新技术,用于对DL SROIQ中表达的本体进行分类。我们开发了一种高效的任务分解算法,用于识别分配给owl2推理器的最小非EL模块,并将大部分工作负载分配给EL推理器。此外,本文还报告了我们的方法在ComR系统中的实现,该系统以黑盒方式集成了两种类型的推理器。实验结果表明,该方法能够合理地分配任务,并能将本体分类的速度提高50%以上。
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