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Sequential Recommendation

Sequential recommendation is a sophisticated approach to providing personalized suggestions by analyzing users' historical interactions in a sequential manner. Unlike traditional recommendation systems, which consider items in isolation, sequential recommendation takes into account the temporal order of user actions. This method is particularly valuable in domains where the sequence of events matters, such as streaming services, e-commerce platforms, and social media.

Papers

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Showing 451–475 of 554 papers

TitleStatusHype
Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-CommerceCode1
RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender SystemCode1
Learning to Learn a Cold-start Sequential Recommender—0
Contrastive Learning for Representation Degeneration Problem in Sequential RecommendationCode1
Self-supervised Learning for Sequential Recommendation with Model Augmentation—0
Extracting Attentive Social Temporal Excitation for Sequential Recommendation—0
Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential RecommendationCode1
A Survey on Reinforcement Learning for Recommender Systems—0
CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation—0
Memory Augmented Multi-Instance Contrastive Predictive Coding for Sequential RecommendationCode1
Black-Box Attacks on Sequential Recommenders via Data-Free Model ExtractionCode1
Lightweight Self-Attentive Sequential Recommendation—0
Is News Recommendation a Sequential Recommendation Task?—0
Personalized next-best action recommendation with multi-party interaction learning for automated decision-making—0
MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation—0
Continuous-Time Sequential Recommendation with Temporal Graph Collaborative TransformerCode1
Contrastive Self-supervised Sequential Recommendation with Robust AugmentationCode1
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models—0
Scene-adaptive Knowledge Distillation for Sequential Recommendation via Differentiable Architecture Search—0
Sequential Recommendation for Cold-start Users with Meta Transitional LearningCode1
Position-enhanced and Time-aware Graph Convolutional Network for Sequential RecommendationsCode1
Sequential Recommendation with Graph Neural NetworksCode1
Improving Sequential Recommendation Consistency with Self-Supervised Imitation—0
Improving Transformer-based Sequential Recommenders through Preference Editing—0
A Large-Scale Rich Context Query and Recommendation Dataset in Online Knowledge-SharingCode1
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