OptiRef: Query Optimization for Knowledge Bases - ANR - Agence nationale de la recherche Accéder directement au contenu
Communication Dans Un Congrès Année : 2023

OptiRef: Query Optimization for Knowledge Bases

Résumé

Ontology-mediated query answering (OMQA) consists in asking database queries on a knowledge base (KB); a KB is a set of facts, the KB's database, described by domain knowledge, the KB's ontology. FOL-rewritability is the main OMQA technique: it reformulates a query w.r.t. the KB's ontology so that the evaluation of the reformulated query on the KB's database computes the correct answers. However, because this technique embeds the domain knowledge relevant to the query into the reformulated query, a reformulated query may be complex and its optimization is the crux of efficiency. We showcase OptiRef that implements a novel, general optimization framework for efficient query answering on datalog+/-, description logic, existential rules, OWL and RDF/S KBs. OptiRef optimizes reformulated queries by rapidly computing, based on a KB's database summary, simpler (contained) queries with the same answers. We demonstrate OptiRef's effectiveness on wellestablished benchmarks: performance is significantly improved in general, up to several orders of magnitude in the best cases!
Fichier principal
Vignette du fichier
www23-author-version.pdf (864.21 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Licence : Copyright (Tous droits réservés)

Dates et versions

hal-04023665 , version 1 (10-03-2023)

Licence

Copyright (Tous droits réservés)

Identifiants

Citer

Wafaa El Husseini, Cheikh Brahim El Vaigh, François Goasdoué, Hélène Jaudoin. OptiRef: Query Optimization for Knowledge Bases. The ACM Web Conference (WWW), Apr 2023, Austin, United States. ⟨10.1145/3543873.3587342⟩. ⟨hal-04023665⟩
62 Consultations
115 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More