对具有标称模式的OWL EL本体进行推理的有效算法

IF 0.7 4区 数学 Q3 COMPUTER SCIENCE, THEORY & METHODS
David Carral;Joseph Zalewski;Pascal Hitzler
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引用次数: 1

摘要

描述逻辑(DL)是Web本体语言(OWL)基础上的知识表示范式。它们提供了DL和规则的非常紧密的集成。名义模式可以理解为OWL之上的语法糖。然而,这种天真的观点导致了低效的推理过程。为了对OWL概要语言OWL EL进行标称模式扩展所产生的${\mathcal {E}\mathcal {L}\mathcal {V}^{++}}$语言开发一个有效的推理过程,我们提出了将${\mathcal {E}\mathcal {L}\mathcal {V}^{++}}$本体转换为可用于可满足性检查和断言检索的类datalog规则程序。使用这种转换可以使用强大的Datalog引擎来解决${\mathcal {E}\mathcal {L}\mathcal {V}^{++}}$本体上的推理任务。我们在几个现实世界的数据密集型本体上实现并评估了我们的方法,并发现它可以胜过最先进的推理器,如Konclude和ELK。作为一个较小的结果,我们还为${\mathcal {E}\mathcal {L}^{++}}$提供了基于规则的算法的自包含描述,它不需要范式转换。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An efficient algorithm for reasoning over OWL EL ontologies with nominal schemas
Nominal schemas have been proposed as an extension to Description Logics (DL), the knowledge representation paradigm underlying the Web Ontology Language (OWL). They provide for a very tight integration of DL and rules. Nominal schemas can be understood as syntactic sugar on top of OWL. However, this naive perspective leads to inefficient reasoning procedures. In order to develop an efficient reasoning procedure for the language ELV ++ , which results from extending the OWL profile language OWL EL with nominal schemas, we propose a transformation from ELV ++ ontologies into Datalog-like rule programs that can be used for satisfiability checking and assertion retrieval. The use of this transformation enables the use of powerful Datalog engines to solve reasoning tasks over ELV ++ ontologies. We implement and then evaluate our approach on several real-world, data-intensive ontologies, and find that it can outperform state-of-the-art reasoners such as Konclude and ELK. As a lesser side result we also provide a self-contained description of a rule-based algorithm for EL ++ which does not require a normal form transformation.
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来源期刊
Journal of Logic and Computation
Journal of Logic and Computation 工程技术-计算机:理论方法
CiteScore
1.90
自引率
14.30%
发文量
82
审稿时长
6-12 weeks
期刊介绍: Logic has found application in virtually all aspects of Information Technology, from software engineering and hardware to programming and artificial intelligence. Indeed, logic, artificial intelligence and theoretical computing are influencing each other to the extent that a new interdisciplinary area of Logic and Computation is emerging. The Journal of Logic and Computation aims to promote the growth of logic and computing, including, among others, the following areas of interest: Logical Systems, such as classical and non-classical logic, constructive logic, categorical logic, modal logic, type theory, feasible maths.... Logical issues in logic programming, knowledge-based systems and automated reasoning; logical issues in knowledge representation, such as non-monotonic reasoning and systems of knowledge and belief; logics and semantics of programming; specification and verification of programs and systems; applications of logic in hardware and VLSI, natural language, concurrent computation, planning, and databases. The bulk of the content is technical scientific papers, although letters, reviews, and discussions, as well as relevant conference reviews, are included.
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