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DOI: 10.4230/OASIcs.ICCSW.2013.19

Generalizing Multi-Context Systems for Reactive Stream Reasoning Applications

Authors: Stefan Ellmauthaler

Published in: OASIcs, Volume 35, 2013 Imperial College Computing Student Workshop

Abstract

In the field of artificial intelligence (AI), the subdomain of knowledge representation (KR) has the aim to represent, integrate, and exchange knowledge in order to do some reasoning about the given information. During the last decades many different KR-languages were proposed for a variety of certain applications with specific needs. The concept of a managed Multi-Context System (mMCS) was introduced to provide adequate formal tools to interchange and integrate knowledge between different KR-approaches. Another arising field of interest in computer science is the design of online applications, which react directly to (possibly infinite) streams of information. This paper presents a genuine approach to generalize mMCS for online applications with continuous streams of information. Our major goal is to find a good tradeoff between expressiveness and computational complexity.

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Stefan Ellmauthaler. Generalizing Multi-Context Systems for Reactive Stream Reasoning Applications. In 2013 Imperial College Computing Student Workshop. Open Access Series in Informatics (OASIcs), Volume 35, pp. 19-26, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2013)

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@InProceedings{ellmauthaler:OASIcs.ICCSW.2013.19,
  author =	{Ellmauthaler, Stefan},
  title =	{{Generalizing Multi-Context Systems for Reactive Stream Reasoning Applications}},
  booktitle =	{2013 Imperial College Computing Student Workshop},
  pages =	{19--26},
  series =	{Open Access Series in Informatics (OASIcs)},
  ISBN =	{978-3-939897-63-7},
  ISSN =	{2190-6807},
  year =	{2013},
  volume =	{35},
  editor =	{Jones, Andrew V. and Ng, Nicholas},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/OASIcs.ICCSW.2013.19},
  URN =		{urn:nbn:de:0030-drops-42675},
  doi =		{10.4230/OASIcs.ICCSW.2013.19},
  annote =	{Keywords: Knowledge Representation, Artificial Intelligence}
}

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Generalizing Multi-Context Systems for Reactive Stream Reasoning Applications

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