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Author

  • Arzamastsev, Alexander A. (1)
  • Hausmann, Verena (1)
  • Kryuchin, Oleg V. (1)
  • Sletkov, Denis V. (1)
  • Troitzsch, Klaus G. (1)
  • Williams, Susan P. (1)
  • Zenkova, Natalia (1)

Year of publication

  • 2011 (1)
  • 2014 (1)

Document Type

  • Part of Periodical (2) (remove)

Keywords

  • classification (2) (remove)

Institute

  • Fachbereich 4 (2) (remove)

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Categorising Social Media Business Risks (2014)
Hausmann, Verena ; Williams, Susan P.
The aim of this paper is to identify and understand the risks and issues companies are experiencing from the business use of social media and to develop a framework for describing and categorising those social media risks. The goal is to contribute to the evolving theorisation of social media risk and to provide a foundation for the further development of social media risk management strategies and processes. The study findings identify thirty risk types organised into five categories (technical, human, content, compliance and reputational). A risk-chain is used to illustrate the complex interrelated, multi-stakeholder nature of these risks and directions for future work are identified.
Simulating medical objects simulation using an artificial neural network whose structure is based on adaptive resonance theory (2011)
Kryuchin, Oleg V. ; Arzamastsev, Alexander A. ; Zenkova, Natalia ; Troitzsch, Klaus G. ; Sletkov, Denis V.
This paper describes artificial neural networks which are based on the adaptive resonance theory. The usage of these artificial neural networks for classification tasks is presented. The example uses is the classification of patient health from the results of general blood analysis.
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