Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia
Moilanen, Mikko; Østbye, Stein; Simonen, Jaakko (2021-06-16)
Moilanen Mikko, Østbye Stein & Simonen Jaakko (2022) Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia, Regional Studies, 56:9, 1429-1441, DOI: 10.1080/00343404.2021.1925237
© 2022 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
https://creativecommons.org/licenses/by/4.0/
https://urn.fi/URN:NBN:fi-fe2022102563275
Tiivistelmä
Abstract
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.
Kokoelmat
- Avoin saatavuus [34589]
