Knowledge Transfer via Pre-training for Recommendation: A Review and Prospect

Recommender systems aim to provide item recommendations for users and are usually faced with data sparsity problems (e.g., cold start) in real-world scenarios. Recently pre-trained models have shown their effectiveness in knowledge transfer between domains and tasks, which can potentially alleviate...

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Detalles Bibliográficos
Autores principales: Zeng, Zheni, Xiao, Chaojun, Yao, Yuan, Xie, Ruobing, Liu, Zhiyuan, Lin, Fen, Lin, Leyu, Sun, Maosong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2021
Materias:
Big Data
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8013982/
https://www.ncbi.nlm.nih.gov/pubmed/33817631
http://dx.doi.org/10.3389/fdata.2021.602071

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8013982/
https://www.ncbi.nlm.nih.gov/pubmed/33817631
http://dx.doi.org/10.3389/fdata.2021.602071

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