Deep Bi-LSTM Networks for Sequential Recommendation

Recent years have seen a surge in approaches that combine deep learning and recommendation systems to capture user preference or item interaction evolution over time. However, the most related work only consider the sequential similarity between the items and neglects the item content feature inform...

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Detalles Bibliográficos
Autores principales: Zhao, Chuanchuan, You, Jinguo, Wen, Xinxian, Li, Xiaowu
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517473/
https://www.ncbi.nlm.nih.gov/pubmed/33286641
http://dx.doi.org/10.3390/e22080870

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7517473/
https://www.ncbi.nlm.nih.gov/pubmed/33286641
http://dx.doi.org/10.3390/e22080870

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