Querying Probabilistic Ontologies with SPARQL

Schönfisch, Jörg

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URL: https://ub-madoc.bib.uni-mannheim.de/36682
Additional URL: http://subs.emis.de/LNI/Proceedings/Proceedings232...
URN: urn:nbn:de:bsz:180-madoc-366825
Document Type: Conference or workshop publication
Year of publication: 2014
Book title: Informatik 2014 - Big Data - Komplexität meistern; Tagung vom 22.-26. September 2014 in Stuttgart
The title of a journal, publication series: GI-Edition : Lecture Notes in Informatics. Proceedings
Volume: 232
Page range: 2245-2256
Date of the conference: 22-26 September 2014
Publisher: Plödereder, Erhard
Place of publication: Bonn
Publishing house: Ges. für Informatik
ISBN: 978-3-88579-626-8
ISSN: 1617-5468
Related URLs:
Publication language: English
Institution: School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Subject: 004 Computer science, internet
Abstract: In recent years a lot of efforts was put into the field of Semantic Web research to specify knowledge as precisely as possible. However, optimizing for precision alone is not sufficient. The handling of uncertain or incomplete information is getting more and more important and it promises to significantly improve the quality of query answering in Semantic Web applications. My plan is to develop a framework that extends the rich semantics offered by ontologies with probabilistic information, stores this in a probabilistic database and provides query answering with the help of query rewriting. In this proposal I describe how these three aspects can be combined. Especially, I am focusing on how uncertainty is incorporated into the ABox and how it is handled by the database and the rewriter during query answering.

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