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M.-P. Andresel, M. Ortiz de la Fuente, M. Simkus:
"Query Rewriting for Ontology-mediated Conditional Answers";
Vortrag: 34th AAAI Conference on Artificial Intelligence (AAAI-20), New York, New York, USA; 07.02.2020 - 12.02.2020; in: "The Thirty-Forth AAAI Conference on Artificial Intelligence, AAAI 2020, New York, New York, USA, February 7 - 12, 2020", V. Conitzer, F. Sha (Hrg.); AAAI-20 Technical Tracks, Vol. 34 No. 03 (2020), S. 2734 - 2741.

Among many proposals for extracting useful answers from incomplete data, ontology-mediated queries (OMQs) use domain knowledge to infer missing facts. We propose an extension of OMQs that allows to make certain assumptions-for example, about parts of the data that may be unavailable at query time, or costly to query-and retrieve conditional answers, that is, tuples that become certain query answers when the assumptions hold. We show that querying in this powerful formalism often has no higher worst-case complexity than in plain OMQs, and that these queries are first-order rewritable for DL-LiteR . Rewritability is preserved even if we use closed predicates to combine the (partial) closed- and open-world assumptions. This is remarkable, since closed predicates are a very useful extension of OMQs, but they make query answering intractable in data complexity even in very restricted settings.

http://dx.doi.org/10.1609/aaai.v34i03.5660

https://doi.org/10.1609/aaai.v34i03.5660

Projektleitung Mantas Simkus:
KtoAPP

Projektleitung Mantas Simkus:
OMEGA