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Emati: a recommender system for biomedical literature based on supervised learning
The scientific literature continues to grow at an ever-increasing rate. Considering that thousands of new articles are published every week, it is obvious how challenging it is to keep up with newly published literature on a regular basis. Using a recommender system that improves the user experience...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2022
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9732843/ https://www.ncbi.nlm.nih.gov/pubmed/36484479 http://dx.doi.org/10.1093/database/baac104 |