优化最具体的概念方法以实现有效的实例检查。

Jia Xu, Patrick Shironoshita, Ubbo Visser, Nigel John, Mansur Kabuka
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引用次数: 0

摘要

实例检查被认为是从描述逻辑(DL)本体中检索数据的中心工具。本文提出了一种改进的最具体概念(MSC)方法,将实例检验转化为包含问题。这种修改后的方法可以生成足够具体的小概念,以回答给定的查询,并允许推理仅探索ABox数据的子集以实现效率。实验结果表明,本文提出的方法在减小概念大小和提高推理效率方面是有效的。
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Optimizing the Most Specific Concept Method for Efficient Instance Checking.

Instance checking is considered a central tool for data retrieval from description logic (DL) ontologies. In this paper, we propose a revised most specific concept (MSC) method for DL SHI, which converts instance checking into subsumption problems. This revised method can generate small concepts that are specific-enough to answer a given query, and allow reasoning to explore only a subset of the ABox data to achieve efficiency. Experiments show effectiveness of our proposed method in terms of concept size reduction and the improvement in reasoning efficiency.

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