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GWAI-87 11th German Workshop on Artifical Intelligence pp 366–385Cite as

Architectural Concepts for Large Knowledge Bases

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Part of the book series: Informatik-Fachberichte ((2252,volume 152))

Abstract

We describe experience in structuring knowledge gained in two parallel projects. Earlier KBMS projects focused on simplifying access and improving the performance of databases using concepts from artificial intelligence. The Rx project developed methods to extract knowledge from databases. Current research (KSYS) exploits this experience to develop and demonstrate new concepts and techniques for managing large collections of knowledge and data.

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Author information

Authors and Affiliations

  1. Computer Science Department, Stanford University, Stanford, California, 94305, USA

    Gio Wiederhold, Surajit Chaudhuri, Waqar Hasan, Michael G. Walker & Marianne Winslett

Authors
  1. Gio Wiederhold
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  2. Surajit Chaudhuri
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  3. Waqar Hasan
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  4. Michael G. Walker
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  5. Marianne Winslett
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Editor information

Editors and Affiliations

  1. Projektgruppe KIT, Sekr. FR 5–8, Technische Universität Berlin, Franklinstraße 28/29, D-1000, Berlin 10, Deutschland

    Katharina Morik

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© 1987 Springer-Verlag Berlin Heidelberg

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Wiederhold, G., Chaudhuri, S., Hasan, W., Walker, M.G., Winslett, M. (1987). Architectural Concepts for Large Knowledge Bases. In: Morik, K. (eds) GWAI-87 11th German Workshop on Artifical Intelligence. Informatik-Fachberichte, vol 152. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-73005-4_39

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  • DOI: https://doi.org/10.1007/978-3-642-73005-4_39

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-18388-4

  • Online ISBN: 978-3-642-73005-4

  • eBook Packages: Springer Book Archive

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