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Formalising Knowledge-Intensive Nuclear Fuel Process Models Using Pattern Theory

  • Conference paper
Knowledge Science, Engineering and Management (KSEM 2011)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7091))

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Abstract

In this paper we present a formalisation for a previously elaborated model-based approach for representing knowledge intensive processes in the domain of nuclear knowledge management. It is shown how a Nuclear Fuel Cycle Process Model can be formalised and represented visually by using the concepts of pattern theory. The formalisation is then applied to the configuration of acquisition paths and the analysis of the evolution of the models. Thereby a basis for the application of formal queries and advanced visual analyses can be established.

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References

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Author information

Authors and Affiliations

  1. Research Group Knowledge Engineering, Faculty of Computer Science, University of Vienna, Bruenner Strasse 72, 1210, Vienna, Austria

    Florin Abazi, Hans-Georg Fill, Wilfried Grossmann & Dimitris Karagiannis

Authors
  1. Florin Abazi
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  2. Hans-Georg Fill
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  3. Wilfried Grossmann
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  4. Dimitris Karagiannis
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Editor information

Editors and Affiliations

  1. Management Science and Information Systems Department, Rutgers, the State University of New Jersey, 1, Washington Park, 07102, Newark, NJ, USA

    Hui Xiong

  2. Department of Industrial and Systems Engineering, The Hong Kong Polytechnic University, Hong Kong, China

    W. B. Lee

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© 2011 Springer-Verlag Berlin Heidelberg

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Abazi, F., Fill, HG., Grossmann, W., Karagiannis, D. (2011). Formalising Knowledge-Intensive Nuclear Fuel Process Models Using Pattern Theory. In: Xiong, H., Lee, W.B. (eds) Knowledge Science, Engineering and Management. KSEM 2011. Lecture Notes in Computer Science(), vol 7091. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25975-3_31

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  • DOI: https://doi.org/10.1007/978-3-642-25975-3_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-25974-6

  • Online ISBN: 978-3-642-25975-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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