We study the separation of positive and negative data examples in terms of description logic concepts in the presence of an ontology. In contrast to previous work, we add a signature that specifies a subset of the symbols that can be used for separation, and we admit individual names in that signature. We consider weak and strong versions of the resulting problem that differ in how the negative examples are treated and we distinguish between separation with and without helper symbols. Within this framework, we compare the separating power of different languages and investigate the complexity of deciding separability. While weak separability is shown to be closely related to conservative extensions, strongly separating concepts coincide with Craig interpolants, for suitably defined encodings of the data and ontology. This enables us to transfer known results from those fields to separability. Conversely, we obtain original results on separability that can be transferred backward. For example, rather surprisingly, conservative extensions and weak separability in ALCO are both 3ExpTime-complete.
翻译:与先前的工作不同,我们增加了一个签名,指定了可用于分离的一组符号,并在该签名中承认了单个名称。我们考虑了由此产生的问题的薄弱和强效版本,这些问题在如何处理负面示例方面各不相同,我们区分了与辅助符号的分离和与辅助符号的分离。在此框架内,我们比较了不同语言的分离力,并调查了决定分离性的复杂性。虽然弱分离性与保守性扩展密切相关,但与克雷格内部插图有强烈的区别,概念与克雷格内部插图相一致,以便适当定义的数据和本体编码。这使我们能够将已知的这些领域成果转移至分离性。相反,我们获得了关于可转移后转移的分离性原始结果。例如,令人惊讶的是,在ALCO中,保守的扩展和薄弱的分离性都是3ExplateTime-compility。