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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Taylor & Francis
2021
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Online Access: | https://hdl.handle.net/10037/22909 https://doi.org/10.1080/00343404.2021.1925237 |
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ftunivtroemsoe:oai:munin.uit.no:10037/22909 2023-05-15T14:23:54+02:00 Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia Moilanen, Mikko Østbye, Stein Jaakko, Simonen 2021-06-16 https://hdl.handle.net/10037/22909 https://doi.org/10.1080/00343404.2021.1925237 eng eng Taylor & Francis Regional studies Moilanen, Østbye, Jaakko. Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia. Regional studies. 2021 FRIDAID 1930061 doi:10.1080/00343404.2021.1925237 0034-3404 1360-0591 https://hdl.handle.net/10037/22909 openAccess Copyright 2021 The Author(s) VDP::Technology: 500::Information and communication technology: 550 VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 Journal article Tidsskriftartikkel Peer reviewed publishedVersion 2021 ftunivtroemsoe https://doi.org/10.1080/00343404.2021.1925237 2021-11-03T23:55:07Z 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. Article in Journal/Newspaper Arctic Arctic University of Tromsø: Munin Open Research Archive Arctic Regional Studies 56 9 1429 1441 |
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Open Polar |
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University of Tromsø: Munin Open Research Archive |
op_collection_id |
ftunivtroemsoe |
language |
English |
topic |
VDP::Technology: 500::Information and communication technology: 550 VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 |
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VDP::Technology: 500::Information and communication technology: 550 VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 Moilanen, Mikko Østbye, Stein Jaakko, Simonen Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia |
topic_facet |
VDP::Technology: 500::Information and communication technology: 550 VDP::Teknologi: 500::Informasjons- og kommunikasjonsteknologi: 550 |
description |
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. |
format |
Article in Journal/Newspaper |
author |
Moilanen, Mikko Østbye, Stein Jaakko, Simonen |
author_facet |
Moilanen, Mikko Østbye, Stein Jaakko, Simonen |
author_sort |
Moilanen, Mikko |
title |
Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia |
title_short |
Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia |
title_full |
Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia |
title_fullStr |
Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia |
title_full_unstemmed |
Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia |
title_sort |
machine learning and the identification of smart specialisation thematic networks in arctic scandinavia |
publisher |
Taylor & Francis |
publishDate |
2021 |
url |
https://hdl.handle.net/10037/22909 https://doi.org/10.1080/00343404.2021.1925237 |
geographic |
Arctic |
geographic_facet |
Arctic |
genre |
Arctic Arctic |
genre_facet |
Arctic Arctic |
op_relation |
Regional studies Moilanen, Østbye, Jaakko. Machine learning and the identification of Smart Specialisation thematic networks in Arctic Scandinavia. Regional studies. 2021 FRIDAID 1930061 doi:10.1080/00343404.2021.1925237 0034-3404 1360-0591 https://hdl.handle.net/10037/22909 |
op_rights |
openAccess Copyright 2021 The Author(s) |
op_doi |
https://doi.org/10.1080/00343404.2021.1925237 |
container_title |
Regional Studies |
container_volume |
56 |
container_issue |
9 |
container_start_page |
1429 |
op_container_end_page |
1441 |
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1766296368496771072 |