A sequel-aware graph neural network that explicitly models item-series relationships improves next-item recommendation on datasets where sequels are common, but it can underperform a strong baseline when sequel information is sparse.
Personalizing session- based recommendations with hierarchical recurrent neural networks
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
cs.IR 1years
2025 1verdicts
REJECT 1representative citing papers
citing papers explorer
-
Heterogeneous Sequel-Aware Graph Neural Networks for Sequential Learning
A sequel-aware graph neural network that explicitly models item-series relationships improves next-item recommendation on datasets where sequels are common, but it can underperform a strong baseline when sequel information is sparse.