The Empirical Robustness of Description Logic Classification
The Empirical Robustness of Description Logic Classification
复制标题
描述逻辑分类的经验稳健性
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
U. Sattler
中科院分区：
文献类型：
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作者：
Rafael S Gonçalves;Nicolas Matentzoglu;B. Parsia;U. Sattler
尽管最近轻量级描述逻辑（DL）的复兴，许多突出的DL，如底层的Web本体语言（OWL），其关键推理服务的最坏情况下的复杂性很高。现代推理机有大量的优化、调优演算和实现技巧，使它们能够在各种应用场景中表现得非常好，即使复杂性结果确保它们在某些输入下表现不佳。对于用户来说，关键问题是他们在实践中遇到这些病态输入的频率，也就是说，推理机的鲁棒性如何。我们试图确定这个问题的分类现有的本体，因为它们是在Web上找到的。作为开发过程的一部分，检查Web上发布的本体是一项相当常见的用户任务。因此，在这种情况下，推理机的健壮性既直接有趣，又为回答更广泛的问题提供了一些提示。从我们的实验中，我们表明，目前的作物的OWL推理，在合作，是非常强大的对网络。
In spite of the recent renaissance in lightweight description logics (DLs), many prominent DLs, such as that underlying the Web Ontology Language (OWL), have high worst case complexity for their key inference services. Modern reasoners have a large array of optimization, tuned calculi, and implementation tricks that allow them to perform very well in a variety of application scenarios, even though the complexity results ensure that they will perform poorly for some inputs. For users, the key question is how often they will encounter those pathological inputs in practice, that is, how robust are reasoners. We attempt to determine this question for classification of existing ontologies as they are found on the Web. It is a fairly common user task to examine ontologies published on the Web as part of their development process. Thus, the robustness of reasoners in this scenario is both directly interesting and provides some hints toward answering the broader question. From our experiments, we show that the current crop of OWL reasoners, in collaboration, is very robust against the Web.
影响因子：
2.5
作者：
Grau, Bernardo Cuenca;Horrocks, Ian;Sattler, Ulrike
通讯作者：
Sattler, Ulrike