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Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology

arXiv 2306.07662 ↗First posted 13 Jun 2023cs.AI cs.DB cs.LOcited by 0

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Abstract (arXiv)

Algorithms for learning database queries from examples and unique characterisations of queries by examples are prominent starting points for developing automated support for query construction and explanation. We investigate how far recent results and techniques on learning and unique characterisations of atemporal queries mediated by an ontology can be extended to temporal data and queries. Based on a systematic review of the relevant approaches in the atemporal case, we obtain general transfer results identifying conditions under which temporal queries composed of atemporal ones are (polynomially) learnable and uniquely characterisable.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 16 of its 74 references that are in the map. First posted on arXiv 13 Jun 2023.

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References · 16

  1. 2018Learning Linear Temporal Propertiescited by 41
  2. 2014The DL-Lite Family and Relationscited by 20
  3. 2013Ontology-based Data Access: A Study through Disjunctive Datalog, CSP, and MMSNPcited by 15
  4. 2021The Complexity of Learning Linear Temporal Formulas from Examplescited by 12
  5. 2021Learning Description Logic Ontologies. Five Approaches. Where Do They Stand?cited by 12
  6. 2017Exact Learning of Lightweight Description Logic Ontologiescited by 10
  7. 2020Logical Separability of Labeled Data Examples under Ontologiescited by 10
  8. 2016The complexity of reverse engineering problems for conjunctive queriescited by 7
  9. 2020Conjunctive Queries: Unique Characterizations and Exact Learnabilitycited by 6
  10. 2023SAT-Based PAC Learning of Description Logic Conceptscited by 5
  11. 2021First-Order Rewritability and Complexity of Two-Dimensional Temporal Ontology-Mediated Queriescited by 4
  12. 2020First Order-Rewritability and Containment of Conjunctive Queries in Horn Description Logicscited by 3
4 more
  1. 2021Actively Learning Concepts and Conjunctive Queries under ELr-Ontologiescited by 3
  2. 2022Frontiers and Exact Learning of ELI Queries under DL-Lite Ontologiescited by 3
  3. 2022Unique Characterisability and Learnability of Temporal Instance Queriescited by 3
  4. 2023Reverse Engineering of Temporal Queries Mediated by LTL Ontologiescited by 1

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