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arXiv · 2306.07662

Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology

Jean Christoph Jung·Vladislav Ryzhikov·Frank Wolter·Michael Zakharyaschev
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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 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.

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Jean Christoph Jung, Vladislav Ryzhikov, Frank Wolter, Michael Zakharyaschev. 2023-06-13. Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology. https://arxiv.org/abs/2306.07662

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