Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia

The European Union (EU) has recognized that universities and research institutes play a critical role in regional Smart Specialisation processes. Our research aims to identify thematic cross-border research domains across space and disciplines in Arctic Scandinavia. We identify potential domains usi...

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Bibliographic Details
Main Authors: Moilanen Mikko (10979012), Østbye Stein (10979015), Simonen Jaakko (10979018)
Format: Other Non-Article Part of Journal/Newspaper
Language:unknown
Published: 2021
Subjects:
O31
R11
R58
Online Access:https://doi.org/10.6084/m9.figshare.14790380.v1
Description
Summary:The European Union (EU) has recognized that universities and research institutes play a critical role in regional Smart Specialisation processes. Our research aims to identify thematic cross-border research domains across space and disciplines in Arctic Scandinavia. We identify potential domains using an unsupervised machine-learning technique (topic modelling). We uncover latent topics based on similarities in the vocabulary of research papers. The proposed methodology can be utilized to identify common research domains across regions and disciplines in almost real time, thereby acting as a decision support system to facilitate cooperation among knowledge producers.