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Description Logics with Abstraction and Refinement

arXiv 2306.03717 ↗First posted 6 Jun 2023cs.AI cs.LOcited by 0

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Abstract (arXiv)

Ontologies often require knowledge representation on multiple levels of abstraction, but description logics (DLs) are not well-equipped for supporting this. We propose an extension of DLs in which abstraction levels are first-class citizens and which provides explicit operators for the abstraction and refinement of concepts and roles across multiple abstraction levels, based on conjunctive queries. We prove that reasoning in the resulting family of DLs is decidable while several seemingly harmless variations turn out to be undecidable. We also pinpoint the precise complexity of our logics and several relevant fragments.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 5 of its 69 references that are in the map. First posted on arXiv 6 Jun 2023.

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References · 5

  1. 2013Ontology-based Data Access: A Study through Disjunctive Datalog, CSP, and MMSNPcited by 15
  2. 2021A Single-Exponential Time 2-Approximation Algorithm for Treewidthcited by 8
  3. 2019An Experimental Study of the Treewidth of Real-World Graph Data (Extended Version)cited by 7
  4. 2013Unary negationcited by 4
  5. 2021How to Approximate Ontology-Mediated Queriescited by 2

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