论文标题
大规模的本体论推理通过Datalog
Large-scale Ontological Reasoning via Datalog
论文作者
论文摘要
一般而言，OWL 2的推理是一项非常昂贵的任务，因此W3C确定了具有良好计算属性的可拖动轮廓。猫头鹰2的许多片段的本体论推理可以简化为数据数据查询的评估。本文调查了其中一些汇编，尤其是针对Horn的查询 - $ \ MATHCAL {SHIQ} $知识库及其在DLV2中的实现，并由新版本的Magic Sets Algorithm所提供。
Reasoning over OWL 2 is a very expensive task in general, and therefore the W3C identified tractable profiles exhibiting good computational properties. Ontological reasoning for many fragments of OWL 2 can be reduced to the evaluation of Datalog queries. This paper surveys some of these compilations, and in particular the one addressing queries over Horn-$\mathcal{SHIQ}$ knowledge bases and its implementation in DLV2 enanched by a new version of the Magic Sets algorithm.
