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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 476–500 of 554 papers

TitleStatusHype
Efficiently Maintaining Next Basket Recommendations under Additions and Deletions of Baskets and ItemsCode0
CSSR: A Context-Aware Sequential Software Service Recommendation ModelCode0
GIMIRec: Global Interaction Information Aware Multi-Interest Framework for Sequential Recommendation—0
Improving Sequential Recommendations via Bidirectional Temporal Data Augmentation with Pre-trainingCode0
DiPS: Differentiable Policy for Sketching in Recommender Systems—0
Gumble Softmax For User Behavior Modeling—0
Edge-Enhanced Global Disentangled Graph Neural Network for Sequential Recommendation—0
Route Optimization via Environment-Aware Deep Network and Reinforcement Learning—0
TEA: A Sequential Recommendation Framework via Temporally Evolving AggregationsCode0
Supervised Advantage Actor-Critic for Recommender Systems—0
Sequential Movie Genre Prediction using Average Transition Probability with Clustering—0
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning—0
Learning to Learn a Cold-start Sequential Recommender—0
Self-supervised Learning for Sequential Recommendation with Model Augmentation—0
Extracting Attentive Social Temporal Excitation for Sequential Recommendation—0
A Survey on Reinforcement Learning for Recommender Systems—0
CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation—0
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
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
Improving Sequential Recommendation Consistency with Self-Supervised Imitation—0
Improving Transformer-based Sequential Recommenders through Preference Editing—0
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