CHOROS 2: Improving the Performance of Qualitative Spatial Reasoning in OWL

N. Mainas, E. Petrakis
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引用次数: 5

Abstract

We investigate on potential improvements to reasoning methods for topological and directional spatial information in OWL. Building upon path consistency, the new reasoner design, referred to as CHOROS 2, suggests several optimizations for reducing the number of compositions of basic relations and for speeding-up its run-time performance. CHOROS 2 serves also as a framework for a realistic evaluation of several alternative reasoner designs discussed in this paper. Perhaps, one of the most interesting alternatives that deserves further investigation relies on the idea of decomposing directional relations into two smaller sets of basic relations yielding fewer compositions. CHOROS 2 infers all implied relations and detects inconsistencies while retaining soundness, completeness and tractability over the supported relations sets. Experimental results demonstrate that all variants of CHOROS 2 run up to several times faster than both CHOROS 1 (its previous implementation) and SOWL, a spatial reasoner implemented in SWRL which runs under Protégé.
CHOROS 2:提高OWL中定性空间推理的性能
我们研究了OWL中拓扑和定向空间信息推理方法的潜在改进。基于路径一致性,新的推理器设计(称为CHOROS 2)提出了一些优化建议,以减少基本关系的组合数量并加快其运行时性能。CHOROS 2也可作为本文中讨论的几种可选推理器设计的现实评估框架。也许,值得进一步研究的最有趣的替代方案之一依赖于将方向关系分解为产生更少组合的两个更小的基本关系集的思想。CHOROS 2推断所有隐含的关系并检测不一致性,同时在支持的关系集上保留稳健性、完整性和可追溯性。实验结果表明,CHOROS 2的所有变体的运行速度都比CHOROS 1(其之前的实现)和SOWL(一个在SWRL中实现的空间推理器)快几倍。
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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