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Deep transfer learning with multimodal embedding to tackle cold-start and sparsity issues in recommendation system
Recommender systems (RSs) have become increasingly vital in the modern information era and connected economy. They play a key role in business operations by generating personalized suggestions and minimizing information overload. However, the performance of traditional RSs is limited by data sparsen...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9410545/ https://www.ncbi.nlm.nih.gov/pubmed/36007091 http://dx.doi.org/10.1371/journal.pone.0273486 |