Inconsistency handling is an important issue in knowledge management. Especially in ontology engineering, logical inconsistencies may occur during ontology construction. A natural way to reason with an inconsistent ontology is to utilize the maximal consistent subsets of the ontology. However, previous studies on selecting maximum consistent subsets have rarely considered the semantics of the axioms, which may result in irrational inference. In this paper, we propose a novel approach to reasoning with inconsistent ontologies in description logics based on the embeddings of axioms. We first give a method for turning axioms into distributed semantic vectors to compute the semantic connections between the axioms. We then define an embedding-based method for selecting the maximum consistent subsets and use it to define an inconsistency-tolerant inference relation. We show the rationality of our inference relation by considering some logical properties. Finally, we conduct experiments on several ontologies to evaluate the reasoning power of our inference relation. The experimental results show that our embedding-based method can outperform existing inconsistency-tolerant reasoning methods based on maximal consistent subsets.

翻译：不一致处理是知识管理中的一个重要问题。特别在本体工程中，本体构建过程中可能产生逻辑不一致性。处理不一致本体的自然方法是利用本体的最大一致子集。然而，以往关于最大一致子集选择的研究很少考虑公理的语义，这可能导致非理性的推理。本文提出了一种基于公理嵌入的描述逻辑中不一致本体推理的新方法。首先，我们给出了一种将公理转化为分布式语义向量的方法，以计算公理之间的语义联系。随后，我们定义了一种基于嵌入的最大一致子集选择方法，并利用它定义了一种不一致容忍的推理关系。通过考察若干逻辑性质，我们证明了该推理关系的合理性。最后，我们在多个本体上进行了实验，评估了该推理关系的推理能力。实验结果表明，基于嵌入的方法在性能上优于现有基于最大一致子集的不一致容忍推理方法。