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Identifying Emerging Technologies and Influential Companies Using Network Dynamics of Patent Clusters

In: Cyberdefense

Author

Listed:
  • Michael Tsesmelis

    (armasuisse Science and Technology)

  • Ljiljana Dolamic

    (armasuisse Science and Technology)

  • Marcus M. Keupp

    (Military Academy at the Swiss Federal Institute of Technology Zurich)

  • Dimitri Percia David

    (University of Applied Sciences Valais)

  • Alain Mermoud

    (armasuisse Science and Technology)

Abstract

The need for dependable and real-time insights on technological paradigm shifts requires objective information. We develop a lean recommender system which predicts emerging technology by a sequential blend of machine learning and network analytics. We illustrate the capabilities of this system with patent data and discuss how it can help organizations make informed decisions.

Suggested Citation

  • Michael Tsesmelis & Ljiljana Dolamic & Marcus M. Keupp & Dimitri Percia David & Alain Mermoud, 2023. "Identifying Emerging Technologies and Influential Companies Using Network Dynamics of Patent Clusters," International Series in Operations Research & Management Science, in: Marcus Matthias Keupp (ed.), Cyberdefense, chapter 0, pages 103-122, Springer.
    • Handle: RePEc:spr:isochp:978-3-031-30191-9_7
    DOI: 10.1007/978-3-031-30191-9_7
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