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Querying with Vague Quantifiers Using Probabilistic Semantics
Verfasser / Verfasserin Hofer, Matthias ; Fermüller, Christian G. ; Ortiz, Magdalena
Erschienen in
Flexible Query Answering Systems - 12th International Conference, FQAS 2017, London, UK, June 21-22, 2017, Proceedings : Christiansen, Henning; Jaudoin, Hélène; Chountas, Panagiotis; Andreasen, Troels; Larsen, Henrik Legind, Cham, 2017, S. 15-27
Erschienen2017
SpracheEnglisch
SerieLecture Notes in Computer Science ; 10333
DokumenttypAufsatz in einem Sammelwerk
Schlagwörter (EN)querying / RDF / semi-fuzzy quantifiers / probabilistic semantics
Projekt-/ReportnummerAustrian Science Fund (FWF): I1897-N25
ISBN9783319596921
URNurn:nbn:at:at-ubtuw:3-3467 Persistent Identifier (URN)
DOI10.1007/978-3-319-59692-1_2 
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Querying with Vague Quantifiers Using Probabilistic Semantics [0.55 mb]
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Many realistic scenarios call for answers to questions involving vague expressions like almost all, about half, or at least about a third. We present a modular extension of classical first-order queries over relational databases, with binary, proportional, semi-fuzzy quantifiers modeling such expressions via random sampling. The extended query language has an intuitive semantics, and allows one to pose natural queries whose answers. This is also demonstrated by experiments with an implementation involving the (geographical) MONDIAL data set.

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