ABox Abduction for Inconsistent Knowledge Bases under Repair Semantics
📰 ArXiv cs.AI
Learn how to apply ABox abduction for inconsistent knowledge bases under repair semantics to resolve non-entailed facts and errors in knowledge bases
Action Steps
- Define the ABox abduction problem for inconsistent knowledge bases under repair semantics
- Identify the non-entailed fact in the knowledge base
- Apply ABox abduction to generate possible extensions of the knowledge base
- Evaluate the generated extensions using repair semantics
- Select the most suitable extension to resolve the non-entailed fact
Who Needs to Know This
This micro-lesson is suitable for AI researchers and knowledge engineers who work with inconsistent knowledge bases and need to apply ABox abduction to resolve errors and non-entailed facts
Key Insight
💡 ABox abduction can be applied to inconsistent knowledge bases under repair semantics to resolve non-entailed facts and errors
Share This
Resolve non-entailed facts in inconsistent knowledge bases using ABox abduction under repair semantics #AI #KnowledgeGraphs
Key Takeaways
Learn how to apply ABox abduction for inconsistent knowledge bases under repair semantics to resolve non-entailed facts and errors in knowledge bases
Full Article
Title: ABox Abduction for Inconsistent Knowledge Bases under Repair Semantics
Abstract:
arXiv:2605.01341v1 Announce Type: cross Abstract: Given a knowledge base (KB) with a non-entailed fact, the ABox abduction problem asks for possible extensions of the KB that would entail this fact. This problem has many applications, ranging from diagnosis to explainability and repair. ABox abduction has been well-investigated for consistent KBs and classical semantics, but little is known for the case of inconsistent KBs, which can be caused by erroneous data. In this paper we define suitable
Abstract:
arXiv:2605.01341v1 Announce Type: cross Abstract: Given a knowledge base (KB) with a non-entailed fact, the ABox abduction problem asks for possible extensions of the KB that would entail this fact. This problem has many applications, ranging from diagnosis to explainability and repair. ABox abduction has been well-investigated for consistent KBs and classical semantics, but little is known for the case of inconsistent KBs, which can be caused by erroneous data. In this paper we define suitable
DeepCamp AI