Rethinking the item order in session-based recommendation with graph neural networks

R Qiu, J Li, Z Huang, H Yin - Proceedings of the 28th ACM international …, 2019 - dl.acm.org
Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …
被引用次数：380 相关文章
[PDF] academia.edu

[PDF][PDF] Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

R Qiu, J Li, Z Huang, H Yin - arXiv preprint arXiv:1911.11942, 2019 - academia.edu
Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …

[引用][C] Rethinking the item order in session-based recommendation with graph neural networks

R Qiu, J Li, Z Huang, H Yin - International Conference on …, 2019 - espace.library.uq.edu.au
Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …

Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

R Qiu, J Li, Z Huang, H Yin - arXiv preprint arXiv:1911.11942, 2019 - arxiv.org
Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …

Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

R Qiu, J Li, Z Huang, H Yin - arXiv e-prints, 2019 - ui.adsabs.harvard.edu
Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …
[PDF] researchgate.net

[PDF][PDF] Rethinking the Item Order in Session-based Recommendation with Graph Neural Networks

R Qiu, J Li, Z Huang, H Yin - arXiv preprint arXiv:1911.11942, 2019 - researchgate.net
Predicting a user's preference in a short anonymous interaction session instead of long-term
history is a challenging problem in the real-life session-based recommendation, eg, e …