SOTAVerified

Session-Based Recommendations

Recommendation based on a sequence of events. e.g. next item prediction

Papers

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Showing 51–75 of 172 papers

TitleStatusHype
G^3SR: Global Graph Guided Session-based Recommendation—0
Exploring Popularity Bias in Session-based Recommendation—0
Exploring Global Information for Session-based Recommendation—0
Graph and Sequential Neural Networks in Session-based Recommendation: A Survey—0
Contrastive Multi-Level Graph Neural Networks for Session-based Recommendation—0
Many-to-one Recurrent Neural Network for Session-based Recommendation—0
Micro-Behavior Encoding for Session-based Recommendation—0
HCGR: Hyperbolic Contrastive Graph Representation Learning for Session-based Recommendation—0
Exploiting Group-level Behavior Pattern forSession-based Recommendation—0
Exploiting Positional Information for Session-based Recommendation—0
Distilling Transitional Pattern to Large Language Models for Multimodal Session-based Recommendation—0
Hierarchical Multi-Task Learning Framework for Session-based Recommendations—0
Augmenting Recurrent Neural Networks with High-Order User-Contextual Preference for Session-Based Recommendation—0
Exploiting Cross-Session Information for Session-based Recommendation with Graph Neural Networks—0
Explainable Session-based Recommendation via Path Reasoning—0
Context-aware short-term interest first model for session-based recommendation—0
Long-Tail Session-based Recommendation from Calibration—0
A Survey on Side Information-driven Session-based Recommendation: From a Data-centric Perspective—0
Learning Similarity among Users for Personalized Session-Based Recommendation from hierarchical structure of User-Session-Item—0
A Graph-based Method for Session-based Recommendations—0
Long-tail Session-based Recommendation—0
M2TRec: Metadata-aware Multi-task Transformer for Large-scale and Cold-start free Session-based Recommendations—0
Language Model Evolutionary Algorithms for Recommender Systems: Benchmarks and Algorithm Comparisons—0
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning—0
Language Models as Recommender Systems: Evaluations and Limitations—0
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