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Attentional factorization machine with review-based user–item interaction for recommendation
In recommender systems, user reviews on items contain rich semantic information, which can express users’ preferences and item features. However, existing review-based recommendation methods either use the static word vector model or cannot effectively extract long sequence features in reviews, resu...
Autores principales: | Li, Zheng, Jin, Di, Yuan, Ke |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10439228/ https://www.ncbi.nlm.nih.gov/pubmed/37596385 http://dx.doi.org/10.1038/s41598-023-40633-4 |
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