Signature-based abduction aims at building hypotheses over a specified set of names, the signature, that explain an observation relative to some background knowledge. This type of abduction is useful for tasks such as diagnosis, where the vocabulary used for observed symptoms differs from the vocabulary expected to explain those symptoms. We present the first complete method solving signature-based abduction for observations expressed in the expressive description logic ALC, which can include TBox and ABox axioms, thereby solving the knowledge base abduction problem. The method is guaranteed to compute a finite and complete set of hypotheses, and is evaluated on a set of realistic knowledge bases.

中文翻译：

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表达性描述逻辑的基于签名的溯因——技术报告

基于签名的溯因旨在在一组指定的名称（签名）上建立假设，以解释与某些背景知识相关的观察结果。这种类型的绑架对于诊断等任务很有用，其中用于观察症状的词汇与预期解释这些症状的词汇不同。我们提出了第一个完整的方法来解决表达描述逻辑 ALC 中表达的观察的基于签名的溯因，它可以包括 TBox 和 ABox 公理，从而解决知识库溯因问题。该方法保证计算一组有限且完整的假设，并在一组现实知识库上进行评估。