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Enumerating Justifications Using Resolution

机译:使用分辨率枚举理由

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If a conclusion follows from a set of axioms, then its justification is a minimal subset of axioms for which the entailment holds. An entailment can have several justifications. Such justifications are commonly used for the purpose of debugging of incorrect entailments in Description Logic ontologies. Recently a number of SAT-based methods have been proposed that can enumerate all justifications for entailments in light-weight ontologies languages, such as EL. These methods work by encoding EL inferences in propositional Horn logic, and finding minimal models that correspond to justifications using SAT solvers. In this paper, we propose a new procedure for enumeration of justifications that uses resolution with answer literals instead of SAT solvers. In comparison to SAT-based methods, our procedure can enumerate justifications in any user-defined order that extends the set inclusion relation. The procedure is easy to implement and, like resolution, can be parametrized with ordering and selection strategies. We have implemented this procedure in PULi - a new Java-based Proof Utility Library, and performed an empirical comparison of (several strategies of) our procedure and SAT-based tools on popular EL ontologies. The experiments show that our procedure provides a comparable, and often better performance than those highly optimized tools. For example, using one of the strategies, we were able for the first time to compute all justifications for all entailed concept subsumptions in one of the largest commonly used medical ontology Snomed CT.
机译:如果结论从一组公理遵循,那么其理由是有关所持有的最小公理子集。征必率可以有几个理由。此类理由通常用于调试描述逻辑本体中不正确的entailments。最近,已经提出了许多基于SAT的方法,可以枚举轻量级本体语言(例如EL)中蕴涵的所有理由。这些方法通过在命题喇叭逻辑中编码EL推断,并找到使用SAT求解器对应的最小模型。在本文中,我们提出了一种新的程序,以枚举使用解决方案的正义,而不是答案文字而不是SAT求解器。与基于SAT的方法相比,我们的过程可以以扩展集合包含关系的任何用户定义的顺序枚举理由。该过程易于实现,并且可以像分辨率一样,可以使用订购和选择策略参数化。我们在Puli实现了这一过程 - 一种基于新的Java的证明实用程序库,并进行了(几个策略)的经验比较,我们的程序和基于SAT基于流行的ELOnolologies的工具。实验表明,我们的程序提供了比那些高度优化的工具的可比性和通常更好的性能。例如,使用其中一个策略,我们首次能够在最大常用的医疗本体中的所有常用医疗本体中的所有必要概念上增生的所有理由中进行计算。

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