Query Optimization for Ontology-Mediated Query Answering
Keywords: Ontology-Mediated Query Answering, FO-rewriting, Query optimization, Query containment, Database summaries
TL;DR: A novel framework that optimizes conjunctive query answering on knowledge bases
Abstract: Ontology-mediated query answering (OMQA) consists in asking database queries on knowledge bases (KBs); a KB is a set of facts called the KB's database, which is described by domain knowledge called the KB's ontology.
A widely-investigated OMQA technique is FO-rewriting: every query asked on a KB is reformulated w.r.t. the KB's ontology, so that the query answers are computed by the relational evaluation of the query reformulation on the KB's database. Crucially, because FO-rewriting compiles the domain knowledge relevant to queries in their reformulations, query reformulations may be complex and their optimization is the crux of efficiency.
We devise a novel optimization framework for a large set of OMQA settings that enjoy FO-rewriting: conjunctive queries, i.e., the core select-project-join queries, asked on KBs expressed in datalog+/- and existential rules, description logic and OWL, or RDF/S.
We optimize the query reformulations produced by state-of-the-art FO-rewriting algorithms by computing rapidly, with the help of a KB's database summary, simpler (contained) queries with same answers that can be evaluated faster by RDBMSs.
We show on a well-established OMQA benchmark that time performance is significantly improved by our optimization framework in general, up to three orders of magnitude.
Track: Semantics and Knowledge
Submission Guidelines Scope: Yes
Submission Guidelines Blind: Yes
Submission Guidelines Format: Yes
Submission Guidelines Limit: Yes
Submission Guidelines Authorship: Yes
Student Author: Yes
Submission Number: 1499
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