基于Horn编译的owl2线性顺序推理逼近

Jianfeng Du, G. Qi, Jeff Z. Pan, Yi-Dong Shen
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引用次数: 1

摘要

为了对不一致的owl2 DL本体进行直接推理,本文考虑了来自命题逻辑的线性顺序推理。这种推理在不一致本体中的结果被定义为在某个一致子本体中的结果。本文提出了一种将OWL - 2dl本体编译为Horn命题程序的新框架,从而可以在多项式时间内从编译的结果近似出用于线性顺序推理的拟一致子本体。提出了一种易于处理的方法来实现该框架。它保证编译后的结果具有多项式大小。实验结果表明,该方法可以准确地计算出几乎所有测试用例的预期子本体,并且比现有的精确方法具有更高的效率和可扩展性。
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Approximating Linear Order Inference in OWL 2 DL by Horn Compilation
In order to directly reason over inconsistent OWL 2 DL ontologies, this paper considers linear order inference which comes from propositional logic. Consequences of this inference in an inconsistent ontology are defined as consequences in a certain consistent sub-ontology. This paper proposes a novel framework for compiling an OWL 2 DL ontology to a Horn propositional program so that the intended consistent sub-ontology for linear order inference can be approximated from the compiled result in polynomial time. A tractable method is proposed to realize this framework. It guarantees that the compiled result has a polynomial size. Experimental results show that the proposed method computes the exact intended sub-ontology for almost all test cases, while it is significantly more efficient and scalable than state-of-the-art exact methods.
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