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Fuzzy Reasoning over RDF Data Using OWL Vocabulary

机译:使用OWL词汇对RDF数据进行模糊推理。

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In this paper, we propose fuzzy pD* semantics which generalizes pD* semantics to reason over fuzzy RDF data using OWL vocabulary. We first define the notions of fuzzy RDF graph and fuzzy pD* interpretation. We then present a set of fuzzy pD*entailment rules and define the Best Degree Bound (BDB) of a triple derived from a fuzzy RDF graph. We show the existence of the BDB of an arbitrary triple. After that, we generalize the partial and full pD* closures to obtain the BDBs of derived triples. We show that the partial fuzzy closure exists and can be computed within polynomial time. Finally, we prove soundness and completeness results for the entailment relation. We also prove that the consistency checking is in P, the entailment is NP-complete, and in P if the target fuzzy RDF graph is ground. Therefore, extending the pD* semantics with fuzzy semantics does not increase the computational complexity.
机译:在本文中,我们提出了模糊pD *语义,该语义将pD *语义概括为使用OWL词汇对模糊RDF数据进行推理的原因。我们首先定义模糊RDF图和模糊pD *解释的概念。然后,我们提出一组模糊pD * enturement规则,并定义从模糊RDF图派生的三元组的最佳度界(BDB)。我们显示了任意三元组的BDB的存在。之后,我们将部分和全部pD *闭包进行泛化以获得派生三元组的BDB。我们表明存在部分模糊闭包,并且可以在多项式时间内进行计算。最后,我们证明了蕴含关系的合理性和完整性。我们还证明了一致性检查在P中进行,意味着是NP完全,如果目标模糊RDF图是地面,则在P中进行了一致性检查。因此,用模糊语义扩展pD *语义不会增加计算复杂性。

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