Research map / Learning theory and algorithms / Combinatorial and search optimization
Learning Query Inseparable εℒℋ Ontologies
Read the paperCheck your idea against 108,967 papers
AI-extracted summary. Written by AI from the paper's title only (no summary yet). Numbers and claims can be wrong or missing context, so check the paper before you cite or build on it.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Use a fixed ABox for equivalence counterexamples | ELH learning with IQs · ELH with IQ, fixed ABox | learning complexity: not in PQueryL -> PTimeL | Helped |
| Restrict conjunctive queries to rooted CQs | ELH query-inseparability learning · ELH with rooted CQs, fixed ABox | learning complexity: not in PQueryL -> PTimeL | Helped |
| Use unrestricted conjunctive queries instead of rooted CQs | ELH query-inseparability learning · ELH with CQs, fixed ABox | learning complexity: PTimeL -> not in PQueryL | Hurt |
| Restrict the hypothesis space to the specified ELH_rhs forms | OMQA PAC learning framework · Restricted ELH_rhs framework with IQs and an added CQ | PAC learnability: not in PQueryL -> polynomial time PAC learnable, even without membership queries | Helped |
| Require updated ABoxes to have individuals bisimilar to individuals in the original ABox | IQ-inseparability under data updates · Updated ABoxes | preservation of IQ-inseparability | Helped |
| Generalize the left-hand sides of learned CIs | ELH IQ-inseparability under data updates · ABoxes in g_T(A*) | learning complexity: PTimeL | Helped |
| Learn using a finite batch of examples whose ABoxes map homomorphically to the fixed ABox | ELH query-inseparability learning · AQ, IQ, or rooted CQs | batch size: polynomial in |T| | Helped |
Closest papers by meaning
- A Model for Learning Description Logic Ontologies Based on Exact Learning (AAAI 2016 · similarity 0.88)
- Consistent Query Answering over Existential Rules with Open and Closed Predicates (AAAI 2025 · similarity 0.83)
- Towards Universal Languages for Tractable Ontology Mediated Query Answering (AAAI 2020 · similarity 0.83)
- Explanations for Inconsistency-Tolerant Query Answering under Existential Rules (AAAI 2020 · similarity 0.83)
- Answering Conjunctive Queries with Safe Negation and Inequalities over RDFS Knowledge Bases (AAAI 2025 · similarity 0.81)
- End-to-End Ontology Learning with Large Language Models (NeurIPS 2024 · similarity 0.81)
Writing a paper in this area? scime draft is a free LaTeX editor with AI included, real-time co-authors and a check of your references and venue rules before you submit. It also imports OpenAI Prism projects.