A Multimodal Machine Learning Approach for Automated Research Software Classification
| dc.rights.license | CC-BY-NC-ND | |
| dc.contributor.advisor | Jansen, Slinger | |
| dc.contributor.author | Bruntink, Britt | |
| dc.date.accessioned | 2025-06-12T23:01:34Z | |
| dc.date.available | 2025-06-12T23:01:34Z | |
| dc.date.issued | 2025 | |
| dc.identifier.uri | https://studenttheses.uu.nl/handle/20.500.12932/49029 | |
| dc.description.sponsorship | Utrecht University | |
| dc.language.iso | EN | |
| dc.subject | This thesis presents a multimodal machine learning pipeline to classify research software and assign it to academic domains. A labeled dataset of research and non-research software was created using automated and manual methods. The models use both README text and repository metadata. The resulting tool enables automated classification and supports better discovery and organization of research software. | |
| dc.title | A Multimodal Machine Learning Approach for Automated Research Software Classification | |
| dc.type.content | Master Thesis | |
| dc.rights.accessrights | Open Access | |
| dc.subject.courseuu | Business Informatics | |
| dc.thesis.id | 46274 |
