Research map / Learning theory and algorithms / Combinatorial and search optimization
Beyond OWL 2 QL in OBDA: Rewritings and Approximations
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Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| compile ontology semantics into mappings (ONTOPROX) instead of ignoring non-DL-Lite axioms | ONTOP · UOBM Qu4 | number of answers: 19 -> 38 | Helped |
| use ONTOPROX instead of LSA/GSA approximation | Telecom queries · Telecom Qt1 | number of answers: 0 -> 82,455 | Helped |
| use ONTOPROX instead of LSA/GSA approximation | Telecom queries · Telecom Qt2 | number of answers: 0 -> 16,487 | Helped |
| use ONTOPROX instead of LSA/GSA | UOBM · UOBM Qu3 | number of answers: 235 -> 247 | Helped |
| use ONTOPROX instead of LSA/GSA | UOBM · UOBM Qu1 | number of answers: 14,197 -> 14,197 | No clear effect |
| use ONTOPROX instead of default ONTOP | Telecom Qt3 · Telecom Qt3 | query time (s): 128 -> 437 | Hurt |
| use ONTOPROX instead of CLIPPER over materialized ABox | UOBM · UOBM Qu4 | query time (s): 21.4 -> 0.52 | Helped |
Closest papers by meaning
- Ontology-Mediated Queries for NOSQL Databases (AAAI 2016 · similarity 0.92)
- Relaxing and Restraining Queries for OBDA (AAAI 2019 · similarity 0.88)
- Query Answering in DL-Lite with Datatypes: A Non-Uniform Approach (AAAI 2017 · similarity 0.87)
- Query Rewriting for Ontology-Mediated Conditional Answers (AAAI 2020 · similarity 0.87)
- Answering Conjunctive Queries with Safe Negation and Inequalities over RDFS Knowledge Bases (AAAI 2025 · similarity 0.85)
- Minimal Macro-Based Rewritings of Formal Languages: Theory and Applications in Ontology Engineering (and Beyond) (AAAI 2024 · similarity 0.82)
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