Simplification of Knowledge Discovery using “Structure Classification”

Zumpe, S.; Esswein, W.

doi:10.1007/978-3-642-55991-4_26

S. Zumpe⁶ &
W. Esswein⁶

Part of the book series: Studies in Classification, Data Analysis, and Knowledge Organization ((STUDIES CLASS))

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Abstract

In order to make pieces of information accessible to a user, they have to be analyzed and structured. Thereby often concepts from the area of Artificial Intelligence (AI), in particular semantic networks, are used. These networks will be extended by using knowledge about meta languages. The paper presents an approach to information structuring. It offers the possibility to cope with highly complex data by using information about the meta-structure of the knowledge base.

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Authors and Affiliations

Chair of Business Informatics esp. System Engineering, Dresden University of Technology, D-01062, Dresden, Germany
S. Zumpe & W. Esswein

Authors

S. Zumpe
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W. Esswein
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Editors and Affiliations

Institute for Decision Theory and Operations Research, University of Karlsruhe, Kaiserstraße 12, 76128, Karlsruhe, Germany
Wolfgang Gaul
Department of Mathematics and Informatics, University of Passau, Innstraße 33, 94030, Passau, Germany
Gunter Ritter

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Zumpe, S., Esswein, W. (2002). Simplification of Knowledge Discovery using “Structure Classification”. In: Gaul, W., Ritter, G. (eds) Classification, Automation, and New Media. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-55991-4_26

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DOI: https://doi.org/10.1007/978-3-642-55991-4_26
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-43233-3
Online ISBN: 978-3-642-55991-4
eBook Packages: Springer Book Archive

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