Tallennettuna:
| Päätekijät: | , , , , |
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| Aineistotyyppi: | Recurso digital |
| Kieli: | |
| Julkaistu: |
Zenodo
2025
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| Aiheet: | |
| Linkit: | https://doi.org/10.5281/zenodo.17385016 |
| Tagit: |
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Sisällysluettelo:
- <p>This collection includes <strong>Python notebooks</strong> (optimised for <strong>Google Colab</strong>) implementing machine learning and natural language processing (NLP) methods for advanced and complex bibliometric data analysis. The scripts automate keyword normalisation, thematic clustering, and topic modelling using <em>spaCy</em>, <em>scikit-learn</em>, and <em>NLTK</em>. Outputs include structured data suitable for bibliometric visualisation and network interpretation. The workflow enhances bibliometric insights by integrating semantic analysis and unsupervised learning, supporting studies in phytochemistry, metabolomics, ethnopharmacology, and related knowledge domains.</p>