Optimizing the Most Specific Concept Method for Efficient Instance Checking.

Jia Xu, Patrick Shironoshita, Ubbo Visser, Nigel John, Mansur Kabuka
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Abstract

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.

Abstract Image

优化最具体的概念方法以实现有效的实例检查。
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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