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DOI: 10.4230/DagSemProc.08091.3
URN: urn:nbn:de:0030-drops-16157
URL: https://drops.dagstuhl.de/opus/volltexte/2008/1615/
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Hitzler, Pascal ; Krötzsch, Markus ; Rudolph, Sebastian ; Tserendorj, Tuvshintur

Approximate OWL Instance Retrieval with SCREECH

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08091.HitzlerPascal.Paper.1615.pdf (0.1 MB)


Abstract

With the increasing interest in expressive ontologies for the Semantic
Web, it is critical to develop scalable and efficient ontology reasoning techniques
that can properly cope with very high data volumes. For certain application domains,
approximate reasoning solutions, which trade soundness or completeness
for increased reasoning speed, will help to deal with the high computational complexities
which state of the art ontology reasoning tools have to face. In this paper,
we present a comprehensive overview of the SCREECH approach to approximate
instance retrieval with OWL ontologies, which is based on the KAON2 algorithms,
facilitating a compilation of OWL DL TBoxes into Datalog, which is
tractable in terms of data complexity. We present three different instantiations
of the Screech approach, and report on experiments which show that the gain in
efficiency outweighs the number of introduced mistakes in the reasoning process.


BibTeX - Entry

@InProceedings{hitzler_et_al:DagSemProc.08091.3,
  author =	{Hitzler, Pascal and Kr\"{o}tzsch, Markus and Rudolph, Sebastian and Tserendorj, Tuvshintur},
  title =	{{Approximate OWL Instance Retrieval with SCREECH}},
  booktitle =	{Logic and Probability for Scene Interpretation},
  pages =	{1--8},
  series =	{Dagstuhl Seminar Proceedings (DagSemProc)},
  ISSN =	{1862-4405},
  year =	{2008},
  volume =	{8091},
  editor =	{Anthony G. Cohn and David C. Hogg and Ralf M\"{o}ller and Bernd Neumann},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/opus/volltexte/2008/1615},
  URN =		{urn:nbn:de:0030-drops-16157},
  doi =		{10.4230/DagSemProc.08091.3},
  annote =	{Keywords: Description logics, automated reasoning, approximate reasoning, Horn logic}
}

Keywords: Description logics, automated reasoning, approximate reasoning, Horn logic
Collection: 08091 - Logic and Probability for Scene Interpretation
Issue Date: 2008
Date of publication: 23.10.2008


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