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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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Bibliografische gegevens
Gepubliceerd in:Entropy (Basel)
Hoofdauteurs: Zhao, Chuanchuan, You, Jinguo, Wen, Xinxian, Li, Xiaowu
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI 2020
Onderwerpen:
Online toegang:https://ncbi.nlm.nih.gov/pmc/articles/PMC7517473/
https://ncbi.nlm.nih.gov/pubmed/33286641
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3390/e22080870
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