Unit, Data Science for Innovation

The research unit “Data Science for Innovation“ develops digital tools for knowledge transfer and thus supports the innovative capacity of industry and research. To this end, the researchers build up an extensive data base and develop intelligent applications based on it using machine learning and network analyses. With their competencies in the field of data science and artificial intelligence, they support other researchers and companies and can contribute significantly to the successful transformation of economic and social structures.

Industry and Research Projects

 

Connect & Collect: AI-powered cloud for interdisciplinary collaborative research and innovation

 

Markets for International Technology Transfer - MarketsFITT

Scientific Library on Regional Development

In this scientific infothek, you will find bundled information on how research contributes to successful structural change. We report on scientific models, instruments and procedures for regional development and transformation processes and the resulting policy advice. This page is updated regularly. If you have any comments, please feel free to contact the editors.

 

Scientific Library on Regional Development

Regional Development and Innovation Policy Division

This research unit belongs to the scientific portfolio of the Regional Development and Innovation Policy Division.

Publications

Jahr
Year
Titel/Autor:in
Title/Author
Publikationstyp
Publication Type
2021 How to Find New Industry Partners for Public Research: A Classification Approach
Trela, Karl; Campbell, Yuri; Dornbusch, Friedrich; Pohle, Anna
Zeitschriftenaufsatz
Journal Article
2021 Ausgründungen aus der außeruniversitären Forschung: Gründungsdynamik und Erfolgsbedingungen im Ost-West-Vergleich
Kahl, Julian; Dornbusch, Friedrich; Pohle, Anna; Trela, Karl; Weiße, Marlen
Studie
Study
2021 Data-driven identification of idioms in song lyrics
Amin, Miriam; Fankhauser, Peter; Kupietz, Marc; Schneider, Roman
Konferenzbeitrag
Conference Paper
2021 Shallow Context Analysis for German Idiom Detection
Amin, Miriam; Fankhauser, Peter; Kupietz, Marc; Schneider, Roman
Vortrag
Presentation
2020 Too big to see: Exploring proxies of structure in a real large-scale university-industry cooperation network
Campbell, Yuri
Vortrag
Presentation
2020 A Survey on Approaches to Computational Humor Generation
Amin, Miriam; Burghardt, M.
Konferenzbeitrag
Conference Paper
Diese Liste ist ein Auszug aus der Publikationsplattform Fraunhofer-Publica

This list has been generated from the publication platform Fraunhofer-Publica

Staff

Research assistants

  • Pier Achkar
  • Anna Rupp
  • Jonas Wolff
  • Marius Zetzsche