KR2024Proceedings of the 21st International Conference on Principles of Knowledge Representation and ReasoningProceedings of the 21st International Conference on Principles of Knowledge Representation and Reasoning

Hanoi, Vietnam. November 2-8, 2024.

Edited by
  1. Pierre Marquis,
  2. Magdalena Ortiz
  3. Maurice Pagnucco

ISSN: 2334-1033
ISBN: 978-1-956792-05-8

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Published by

Copyright © 2024 International Joint Conferences on Artificial Intelligence Organization

Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology

  1. Jean Christoph Jung(TU Dortmund)
  2. Vladislav Ryzhikov(Birkbeck, University of London)
  3. Frank Wolter(University of Liverpool)
  4. Michael Zakharyaschev(Birkbeck, University of London)
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BibTeX
https://doi.org/10.24963/kr.2024/46

Keywords

  1. Description logics-General
  2. Geometric, spatial, and temporal reasoning-General

Abstract

Algorithms for learning database queries from examples and unique characterisations of queries by examples are prominent starting points for developing automated support for query explanation and construction. 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.