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Did I Damage my Ontology? A Case for Conservative Extensions in Description Logic

机译:我损坏了我的本体论吗?描述逻辑中保守扩展的案例

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In computer science, ontologies are dynamic entities: to adapt them to new and evolving applications, it is necessary to frequently perform modifications such as the extension with new axioms and merging with other ontologies. We argue that, after performing such modifications, it is important to know whether the resulting ontology is a conservative extension of the original one. If this is not the case, then there may be unexpected consequences when using the modified ontology in place of the original one in applications. In this paper, we propose and investigate new reasoning problems based on the notion of conservative extension, assuming that ontologies are formulated as TBoxes in the description logic ALC. We show that the fundamental such reasoning problems are decidable and 2EXPTIME-complete. Additionally, we perform a finer-grained analysis that distinguishes between the size of the original ontology and the size of the additional axioms. In particular, we show that there are algorithms whose runtime is 'only' exponential in the size of the original ontology, but double exponential in the size of the added axioms. If the size of the new axioms is small compared to the size of the ontology, these algorithms are thus not significantly more complex than the standard reasoning services implemented in modern description logic reasoners. If the extension of an ontology is not conservative, our algorithm is capable of computing a concept that witnesses non-conservativeness. We show that the computed concepts are of (worst-case) minimal size.
机译:在计算机科学中,本体是动态实体:要使它们适应新的和不断发展的应用程序,有必要经常使用新的公理进行诸如扩展之类的修改并与其他本体合并。我们认为,在执行此类修改后,重要的是要知道所产生的本体是原始的保守延伸。如果不是这种情况,那么在使用修改后的本体代替应用程序中时可能存在意外后果。在本文中,我们提出并根据保守延伸的概念提出新的推理问题,假设本体在描述逻辑ALC中作为TboxES制定为Tboxes。我们表明,这一基本的推理问题是可判定的和2次封面。此外,我们执行更精细的分析,该分析可以区分原始本体的大小和附加公理的尺寸。特别是,我们表明,存在的算法,其运行时在原始本体的大小中“仅”指数,而是在添加的公理的大小的双指数。如果新公理的大小与本体的大小相比,这些算法比在现代描述逻辑推理仪中实现的标准推理服务并不明显更复杂。如果本体的扩展不是保守的,我们的算法能够计算目击不保守的概念。我们表明计算的概念是(最差的情况)最小的大小。

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