AILOJul 26, 2024

Repairing Networks of $\mathcal{EL_\perp}$ Ontologies using Weakening and Completing -- Extended version

arXiv:2407.18848v1h-index: 33
Originality Synthesis-oriented
AI Analysis

This work addresses the issue of maintaining correct domain consequences in ontology networks for semantics-based applications, representing an incremental improvement over traditional debugging techniques.

The paper tackles the problem of repairing ontology networks by introducing a framework that includes debugging, weakening, and completing operations to avoid removing correct consequences, and presents an implemented tool to demonstrate its influence on network quality.

The quality of ontologies and their alignments is crucial for developing high-quality semantics-based applications. Traditional debugging techniques repair ontology networks by removing unwanted axioms and mappings, but may thereby remove consequences that are correct in the domain of the ontology network. In this paper we propose a framework for repairing ontology networks that deals with this issue. It defines basic operations such as debugging, weakening and completing. Further, it defines combination operators that reflect choices in how and when to use the basic operators, as well as choices regarding the autonomy level of the ontologies and alignments in the ontology network. We show the influence of the combination operators on the quality of the repaired network and present an implemented tool. By using our framework together with existing algorithms for debugging, weakening and completing, we essentially provide a blueprint for extending previous work and systems.

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