Graph Neural Network-Guided Contrastive Learning for Sequential Recommendation

Sequential recommendation uses contrastive learning to randomly augment user sequences and alleviate the data sparsity problem. However, there is no guarantee that the augmented positive or negative views remain semantically similar. To address this issue, we propose graph neural network-guided cont...

Descripción completa

Detalles Bibliográficos
Autores principales: Yang, Xing-Yao, Xu, Feng, Yu, Jiong, Li, Zi-Yang, Wang, Dong-Xiao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Communication
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303316/
https://www.ncbi.nlm.nih.gov/pubmed/37420737
http://dx.doi.org/10.3390/s23125572

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10303316/
https://www.ncbi.nlm.nih.gov/pubmed/37420737
http://dx.doi.org/10.3390/s23125572

Ejemplares similares