# Reverse Engineering of Temporal Queries Mediated by LTL Ontologies

arXiv: https://arxiv.org/abs/2305.01248 · HTML: https://mlsanity.com/paper/2305.01248/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 13 of its 79 references that are in the map.
- First posted on arXiv 2 May 2023.

## Builds on (most cited first, 13 of 13)

- [Learning Linear Temporal Properties](https://mlsanity.com/paper/1806.03953/) (2018)
- [Efficient Concept Induction for Description Logics](https://mlsanity.com/paper/1812.03243/) (2018)
- [EvoLearner: Learning Description Logics with Evolutionary Algorithms](https://mlsanity.com/paper/2111.04879/) (2021)
- [The Complexity of Learning Linear Temporal Formulas from Examples](https://mlsanity.com/paper/2102.00876/) (2021)
- [Logical Separability of Labeled Data Examples under Ontologies](https://mlsanity.com/paper/2007.01610/) (2020)
- [Scalable Anytime Algorithms for Learning Fragments of Linear Temporal Logic](https://mlsanity.com/paper/2110.06726/) (2021)
- [The complexity of reverse engineering problems for conjunctive queries](https://mlsanity.com/paper/1606.01206/) (2016)
- [Extremal Fitting Problems for Conjunctive Queries](https://mlsanity.com/paper/2206.05080/) (2022)
- [Separating Data Examples by Description Logic Concepts with Restricted Signatures](https://mlsanity.com/paper/2107.05285/) (2021)
- [First-Order Rewritability and Complexity of Two-Dimensional Temporal Ontology-Mediated Queries](https://mlsanity.com/paper/2111.06806/) (2021)
- [First-Order Rewritability of Ontology-Mediated Queries in Linear Temporal Logic](https://mlsanity.com/paper/2004.07221/) (2020)
- [Unique Characterisability and Learnability of Temporal Instance Queries](https://mlsanity.com/paper/2205.01651/) (2022)
- [Separating Regular Languages with First-Order Logic](https://mlsanity.com/paper/1402.3277/) (2014)

## Built on by (most cited first, 1 of 1)

- [Unique Characterisability and Learnability of Temporal Queries Mediated by an Ontology](https://mlsanity.com/paper/2306.07662/) (2023)

## 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.