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...

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Detalles Bibliográficos
Autores principales: Kart, Özge, Mestiashvili, Alexandre, Lachmann, Kurt, Kwasnicki, Richard, Schroeder, Michael
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2022
Materias:
Original Article
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

Internet

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

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