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http://hdl.handle.net/11366/2502| Title: | A machine-learning approach for a CRIS research outputs’ SDG classifications | Authors: | Lopes, António Luís Roseta-Palma, Caterina Simaens, Ana |
Keywords: | research information management;current research information systems;Sustainable Development Goals (SDGs);research classifications;machine learning;Ciência-IUL | Issue Date: | 23-Nov-2023 | Publisher: | euroCRIS | Conference: | Strategic Membership Meeting 2023 – Autumn (Pamplona) | Abstract: | This presentation takes stock of the methodologies that have been applied to the assessment of research outputs as they relate to the SDGs, in our institutional CRIS, Ciência-IUL. In particular, we focus on the machine-learning-based approach that was employed in the CRIS to help researchers choose the right SDGs to be associated with their research outputs (including publications and projects). |
Description: | 20 slides.-- Presentation delivered by António Lopes within session "Contributions from euroCRIS members".-- Includes extended abstract submitted to the event |
URI: | http://hdl.handle.net/11366/2502 |
| Appears in Collections: | Conference |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| euroCRIS_SMM2023Pamplona_ALopes_A-machine-learning-approach.pdf | PDF presentation | 1.11 MB | Adobe PDF | View/Open |
| euroCRIS_SMM2023-ISCTE-IUL-ALopes-extended-abstract.pdf | Extended abstract | 778.64 kB | Adobe PDF | View/Open |
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