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  Counting Query Answers over a DL-Lite Knowledge Base

Calvanes, D., Corman, J., Lanti, D., & Razniewski, S. (2020). Counting Query Answers over a DL-Lite Knowledge Base. In C. Bessiere (Ed.), Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence (pp. 1658-1666). IJCAI. doi:10.24963/ijcai.2020/230.

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Basisdaten

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Genre: Konferenzbeitrag
Latex : Counting Query Answers over a {$DL-Lite$} Knowledge Base

Externe Referenzen

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Urheber

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 Urheber:
Calvanes, Diego1, Autor
Corman, Julien1, Autor
Lanti, Davide1, Autor
Razniewski, Simon2, Autor           
Affiliations:
1External Organizations, ou_persistent22              
2Databases and Information Systems, MPI for Informatics, Max Planck Society, ou_24018              

Inhalt

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Schlagwörter: Computer Science, Databases, cs.DB,Computer Science, Artificial Intelligence, cs.AI
 Zusammenfassung: Counting answers to a query is an operation supported by virtually all
database management systems. In this paper we focus on counting answers over a
Knowledge Base (KB), which may be viewed as a database enriched with background
knowledge about the domain under consideration. In particular, we place our
work in the context of Ontology-Mediated Query Answering/Ontology-based Data
Access (OMQA/OBDA), where the language used for the ontology is a member of the
DL-Lite family and the data is a (usually virtual) set of assertions. We study
the data complexity of query answering, for different members of the DL-Lite
family that include number restrictions, and for variants of conjunctive
queries with counting that differ with respect to their shape (connected,
branching, rooted). We improve upon existing results by providing a PTIME and
coNP lower bounds, and upper bounds in PTIME and LOGSPACE. For the latter case,
we define a novel query rewriting technique into first-order logic with
counting.

Details

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Sprache(n): eng - English
 Datum: 20202020
 Publikationsstatus: Online veröffentlicht
 Seiten: -
 Ort, Verlag, Ausgabe: -
 Inhaltsverzeichnis: -
 Art der Begutachtung: -
 Identifikatoren: BibTex Citekey: RazniewskiIJCAI2020
DOI: 10.24963/ijcai.2020/230
 Art des Abschluß: -

Veranstaltung

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Titel: Twenty-Ninth International Joint Conference on Artificial Intelligence
Veranstaltungsort: Yokohama, Japan (Virtual)
Start-/Enddatum: 2021-01-07 - 2021-01-15

Entscheidung

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Projektinformation

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Quelle 1

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Titel: Proceedings of the Twenty-Ninth International Joint Conference on Artificial Intelligence
  Kurztitel : IJCAI 2020
Genre der Quelle: Konferenzband
 Urheber:
Bessiere, Christian1, Herausgeber
Affiliations:
1 External Organizations, ou_persistent22            
Ort, Verlag, Ausgabe: IJCAI
Seiten: - Band / Heft: - Artikelnummer: - Start- / Endseite: 1658 - 1666 Identifikator: ISBN: 978-0-9992411-6-5