Several types of dependencies have been proposed for the static analysis of existential rule ontologies, promising insights about computational properties and possible practical uses of a given set of rules, e.g., in ontology-based query answering. Unfortunately, these dependencies are rarely implemented, so their potential is hardly realised in practice. We focus on two kinds of rule dependencies -- positive reliances and restraints -- and design and implement optimised algorithms for their efficient computation. Experiments on real-world ontologies of up to more than 100,000 rules show the scalability of our approach, which lets us realise several previously proposed applications as practical case studies. In particular, we can analyse to what extent rule-based bottom-up approaches of reasoning can be guaranteed to yield redundancy-free "lean" knowledge graphs (so-called cores) on practical ontologies.
翻译:为了静态分析存在规则的内涵,提出了几类依赖性建议,对存在规则的内涵进行静态分析,对计算特性和某一套规则的可能实际使用,例如,在基于本体学的问答中,对某一套规则的计算特性和可能的实用用途有很有希望的洞察力。不幸的是,这些依赖性很少得到落实,因此其潜力实际上难以实现。我们侧重于两种类型的规则依赖性 -- -- 积极的依赖性和约束性 -- -- 以及设计和实施优化算法以有效计算这些规则。关于多达10万多条规则的实际世界内涵的实验显示了我们的方法的可扩展性,这使我们能够实现以前提出的若干应用,作为实际案例研究。特别是,我们可以分析在多大程度上可以保证基于规则的自下而上推理方法能够产生关于实际理论的无冗余的“精度”知识图表(所谓的核心)。