License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
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DOI: 10.4230/OASIcs.ICCSW.2013.19
URN: urn:nbn:de:0030-drops-42675
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Ellmauthaler, Stefan

Generalizing Multi-Context Systems for Reactive Stream Reasoning Applications

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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.

BibTeX - Entry

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

Keywords: Knowledge Representation, Artificial Intelligence
Collection: 2013 Imperial College Computing Student Workshop
Issue Date: 2013
Date of publication: 14.10.2013

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