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Goal-Directed Module Extraction for Explaining OWL DL Entailments

机译:目标导向的模块提取,用于解释OWL DL需求

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摘要

Module extraction methods have proved to be effective in improving the performance of some ontology reasoning tasks, including finding justifications to explain why an entailment holds in an OWL DL ontology. However, the existing module extraction methods that compute a syntactic locality-based module for the sub-concept in a subsumption entailment, though ensuring the resulting module to preserve all justifications of the entailment, may be insufficient in improving the performance of finding all justifications. This is because a syntactic locality-based module is independent of the super-concept in a sub-sumption entailment and always contains all concept/role assertions. In order to extract smaller modules to further optimize finding all justifications in an OWL DL ontology, we propose a goal-directed method for extracting a module that preserves all justifications of a given entailment. Experimental results on large ontologies show that a module extracted by our method is smaller than the corresponding syntactic locality-based module, making the subsequent computation of all justifications more scalable and more efficient.
机译:事实证明,模块提取方法可以有效地改善某些本体推理任务的性能,包括找到理由来解释为什么OWL DL本体中包含某种必要条件。但是,现有的模块提取方法虽然可以确保生成的模块保留该包含条件的所有理由,但在包含蕴含条件中为子概念计算基于句法局部性的模块,可能不足以提高查找所有理由的性能。这是因为基于句法局部性的模块在包含子需求中独立于超概念,并且始终包含所有概念/角色声明。为了提取较小的模块以进一步优化查找OWL DL本体中的所有理由,我们提出了一种目标定向方法,用于提取保留给定蕴藏条件的所有理由的模块。在大型本体上的实验结果表明,我们的方法所提取的模块比相应的基于句法局部性的模块要小,从而使所有证明的后续计算更具可扩展性和效率。

著录项

  • 来源
    《The semantic web - ISWC 2009》|2009年|P.163-179|共17页
  • 会议地点 Chantilly VA(US);Chantilly VA(US)
  • 作者

    Jianfeng Du; Guilin Qi; Qiu Ji;

  • 作者单位

    Institute of Business Intelligence and Knowledge Discovery, Guangdong University of Foreign Studies, Guangzhou 510006, China State Key Laboratory of Computer Science, Institute of Software, Chinese Academy of Sciences, Beijing 100190, China;

    rnAIFB, Universitaet Karlsruhe, D-76128 Karlsruhe, Germany School of Computer Science and Engineering, Southeast University, Nanjing, China;

    rnAIFB, Universitaet Karlsruhe, D-76128 Karlsruhe, Germany;

  • 会议组织
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 计算机网络;
  • 关键词

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