Using machine learning to predict the evolution of physics research
The advancement of science, as outlined by Popper and Kuhn, is largely qualitative, but with bibliometric data, it is possible and desirable to develop a quantitative picture of scientific progress. Furthermore, it is also important to allocate finite resources to research topics that have the growt...
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| Format: | Journal Article |
| Sprache: | English |
| Veröffentlicht: |
2021
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| Online Zugang: | https://hdl.handle.net/10356/146342 |