mlsanityData to 7 Oct 2026

Reverse Engineering of Temporal Queries Mediated by LTL Ontologies

arXiv 2305.01248 ↗First posted 2 May 2023cs.LO cs.AIcited by 1

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Abstract (arXiv)

In reverse engineering of database queries, we aim to construct a query from a given set of answers and non-answers; it can then be used to explore the data further or as an explanation of the answers and non-answers. We investigate this query-by-example problem for queries formulated in positive fragments of linear temporal logic LTL over timestamped data, focusing on the design of suitable query languages and the combined and data complexity of deciding whether there exists a query in the given language that separates the given answers from non-answers. We consider both plain LTL queries and those mediated by LTL-ontologies.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 13 of its 79 references that are in the map. First posted on arXiv 2 May 2023.

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13 of 79 references.

References · 13

  1. 2018Learning Linear Temporal Propertiescited by 41
  2. 2018Efficient Concept Induction for Description Logicscited by 17
  3. 2021EvoLearner: Learning Description Logics with Evolutionary Algorithmscited by 17
  4. 2021The Complexity of Learning Linear Temporal Formulas from Examplescited by 12
  5. 2020Logical Separability of Labeled Data Examples under Ontologiescited by 10
  6. 2021Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logiccited by 9
  7. 2016The complexity of reverse engineering problems for conjunctive queriescited by 7
  8. 2022Extremal Fitting Problems for Conjunctive Queriescited by 6
  9. 2021Separating Data Examples by Description Logic Concepts with Restricted Signaturescited by 5
  10. 2021First-Order Rewritability and Complexity of Two-Dimensional Temporal Ontology-Mediated Queriescited by 4
  11. 2020First-Order Rewritability of Ontology-Mediated Queries in Linear Temporal Logiccited by 3
  12. 2022Unique Characterisability and Learnability of Temporal Instance Queriescited by 3
1 more
  1. 2014Separating Regular Languages with First-Order Logiccited by 1

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Citing papers per year: 2023: 1.

1 paper.

  1. 2023Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontologycited by 0