Given a knowledge base and an observation as a set of facts, ABox abduction aims at computing a hypothesis that, when added to the knowledge base, is sufficient to entail the observation. In signature-based ABox abduction, the hypothesis is further required to use only names from a given set. This form of abduction has applications such as diagnosis, KB repair, or explaining missing entailments. It is possible that hypotheses for a given observation only exist if we admit the use of fresh individuals and/or complex concepts built from the given signature, something most approaches for ABox abduction so far do not support or only support with restrictions. In this paper, we investigate the computational complexity of this form of abduction -- allowing either fresh individuals, complex concepts, or both -- for various description logics, and give size bounds on the hypotheses if they exist.

中文翻译：

---

基于签名的绑架，带有新鲜的个体和描述逻辑的复杂概念（扩展版）

给定一个知识库和作为一组事实的观察结果，ABox绑架的目的是计算一个假设，将其添加到知识库中就足以进行观察。在基于签名的ABox绑架中，进一步要求假设仅使用给定集合中的名称。这种绑架形式具有诊断，知识库修复或解释遗失物等应用。仅当我们允许使用新鲜的个体和/或根据给定签名构建的复杂概念时，才可能存在给定观察结果的假设，到目前为止，大多数ABox绑架方法都不支持或仅带有限制条件。在本文中，我们研究了这种绑架形式的计算复杂性-允许新鲜的个体，复杂的概念或同时允许这两种形式-用于各种描述逻辑，