Cost-Based Semantics for Querying Inconsistent Weighted Knowledge Bases
Abstract
In this paper, we explore a quantitative approach to querying inconsistent description logic knowledge bases. We consider weighted knowledge bases in which both axioms and assertions have (possibly infinite) weights, which are used to assign a cost to each interpretation based upon the axioms and assertions it violates. Two notions of certain and possible answer are defined by either considering interpretations whose cost does not exceed a given bound or restricting attention to optimal-cost interpretations. Our main contribution is a comprehensive analysis of the combined and data complexity of bounded cost satisfiability and certain and possible answer recognition, for description logics between ELbot and ALCO.
Cite
@article{arxiv.2407.20754,
title = {Cost-Based Semantics for Querying Inconsistent Weighted Knowledge Bases},
author = {Meghyn Bienvenu and Camille Bourgaux and Robin Jean},
journal= {arXiv preprint arXiv:2407.20754},
year = {2024}
}
Comments
This is an extended version of a paper appearing at the 21st International Conference on Principles of Knowledge Representation and Reasoning (KR 2024). 20 pages