一句话：提出利用概率语义 DISPONTE 查询不一致描述逻辑知识库，并在 TRILL/BUNDLE 中实现且与修复语义比较。
语义网中的描述逻辑知识库常因多源、动态和相互矛盾的信息而不一致，经典推理算法无法直接处理，只能先调试消除不一致。本文利用已有的概率语义 DISPONTE 为不一致知识库中的查询提供语义基础：当知识库不一致时，不再强制删除公理，而是让公理带有不确定性，通过概率推理回答查询。作者在 TRILL 和 BUNDLE 推理器中实现了该方法，并进行了实验评估；此外还将所提方法与修复语义（repair semantics）进行了形式化比较，说明其在处理不一致查询任务上的有效性与特点。
The necessity to manage inconsistency in Description Logics Knowledge Bases (KBs) has come to the fore with the increasing importance gained by the Semantic Web, where information comes from different sources that constantly change their content and may contain contradictory descriptions when considered either alone or together. Classical reasoning algorithms do not handle inconsistent KBs, forcing the debugging of the KB in order to remove the inconsistency. In this paper, we exploit an existing probabilistic semantics called DISPONTE to overcome this problem and allow queries also in case of inconsistent KBs. We implemented our approach in the reasoners TRILL and BUNDLE and empirically tested the validity of our proposal. Moreover, we formally compare the presented approach to that of the repair semantics, one of the most established semantics when considering DL reasoning tasks.
DOI 原文 · arXiv · PDF（开放获取） · DBLP
@article{abs-2306-09138,
title = {Exploiting Uncertainty for Querying Inconsistent Description Logics Knowledge Bases},
author = {Riccardo Zese and Evelina Lamma and Fabrizio Riguzzi},
journal = {Logical Methods in Computer Science},
volume = {Volume 21, Issue 3},
year = {2025},
doi = {10.46298/lmcs-21(3:14)2025}
}