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Characterizing the Program Expressive Power of Existential Rule Languages
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by
Heng Zhang,
Guifei Jiang
Published
in PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE
by Association for the Advancement of Artificial Intelligence (AAAI).
2022 Volume 36, p5950-5957
Abstract
Existential rule languages are a family of ontology languages that have been widely used in ontology-mediated query answering (OMQA). However, for most of them, the expressive power of representing domain knowledge for OMQA, known as the program expressive power, is not well-understood yet. In this paper, we establish a number of novel characterizations for the program expressive power of several important existential rule languages, including tuple-generating dependencies (TGDs), linear TGDs, as well as disjunctive TGDs. The characterizations employ natural model-theoretic properties, and automata-theoretic properties sometimes, which thus provide powerful tools for identifying the definability of domain knowledge for OMQA in these languages.
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Crossref Metadata (via API)
Worldcat
SHERPA/RoMEO (journal policies)
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Semantic Scholar
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