利用_ (_)_ (_)wer推理器进行具有值限制的高效TBox推理

IF 1.4 2区 数学 Q3 COMPUTER SCIENCE, SOFTWARE ENGINEERING
F. Baader, P. Koopmann, Friedrich Michel, Anni-Yasmin Turhan, Benjamin Zarrieß
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引用次数: 1

摘要

无表达描述逻辑(DL) ${\cal F}{{\cal L}_0}$以连接和值限制作为其唯一的概念构造函数,当发现在${\cal F}{{\cal L}_0}$ w.r.t. general TBoxes中的推理是ExpTime-complete时,它就声名狼藉了,也就是说,它和在更具表达性的逻辑${\cal A}{\cal L}{\cal C}$中的推理一样困难。在本文中,我们通过提出${\cal F}{{\cal L}_0}$的专用包容算法来恢复${\cal F}{{\cal L}_0}$,该算法比高度优化的深度学习推理器使用的基于表的算法简单得多。我们的实验表明,在我们的${\cal F}{{\cal L}_0}$ wer推理器中原型实现的新算法的性能与高度优化的推理器的性能相比非常好。${\cal F}{{\cal L}_0}$ wer也可以处理用${\cal F}{{\cal L}_0}$的扩展${\cal F}{{\cal L}_ \bot}$编写的本体,采用本文所示的多项式时间约简,消除了顶部和底部的概念。我们还研究了与${\cal F}{{\cal L}_0}$和${\cal F}{{\cal L}_ \bot}$的角片段相关的dl推理的复杂性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Efficient TBox Reasoning with Value Restrictions using the ℱℒ0wer reasoner
The inexpressive Description Logic (DL) ${\cal F}{{\cal L}_0}$ , which has conjunction and value restriction as its only concept constructors, had fallen into disrepute when it turned out that reasoning in ${\cal F}{{\cal L}_0}$ w.r.t. general TBoxes is ExpTime-complete, that is, as hard as in the considerably more expressive logic ${\cal A}{\cal L}{\cal C}$ . In this paper, we rehabilitate ${\cal F}{{\cal L}_0}$ by presenting a dedicated subsumption algorithm for ${\cal F}{{\cal L}_0}$ , which is much simpler than the tableau-based algorithms employed by highly optimized DL reasoners. Our experiments show that the performance of our novel algorithm, as prototypically implemented in our ${\cal F}{{\cal L}_0}$ wer reasoner, compares very well with that of the highly optimized reasoners. ${\cal F}{{\cal L}_0}$ wer can also deal with ontologies written in the extension ${\cal F}{{\cal L}_ \bot }$ of ${\cal F}{{\cal L}_0}$ with the top and the bottom concept by employing a polynomial-time reduction, shown in this paper, which eliminates top and bottom. We also investigate the complexity of reasoning in DLs related to the Horn-fragments of ${\cal F}{{\cal L}_0}$ and ${\cal F}{{\cal L}_ \bot }$ .
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来源期刊
Theory and Practice of Logic Programming
Theory and Practice of Logic Programming 工程技术-计算机:理论方法
CiteScore
4.50
自引率
21.40%
发文量
40
审稿时长
>12 weeks
期刊介绍: Theory and Practice of Logic Programming emphasises both the theory and practice of logic programming. Logic programming applies to all areas of artificial intelligence and computer science and is fundamental to them. Among the topics covered are AI applications that use logic programming, logic programming methodologies, specification, analysis and verification of systems, inductive logic programming, multi-relational data mining, natural language processing, knowledge representation, non-monotonic reasoning, semantic web reasoning, databases, implementations and architectures and constraint logic programming.
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