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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 401–425 of 554 papers

TitleStatusHype
Sequential Search with Off-Policy Reinforcement Learning—0
Maximizing Cumulative User Engagement in Sequential Recommendation: An Online Optimization Perspective—0
Similarity-Guided Diffusion for Contrastive Sequential Recommendation—0
Measuring Recency Bias In Sequential Recommendation Systems—0
Transferable Sequential Recommendation via Vector Quantized Meta Learning—0
Memory efficient location recommendation through proximity-aware representation—0
Slow Thinking for Sequential Recommendation—0
Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation—0
TRec: Sequential Recommender Based On Latent Item Trend Information—0
SPMC: Socially-Aware Personalized Markov Chains for Sparse Sequential Recommendation—0
MLSA4Rec: Mamba Combined with Low-Rank Decomposed Self-Attention for Sequential Recommendation—0
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation—0
Modeling Domain and Feedback Transitions for Cross-Domain Sequential Recommendation—0
Modeling Multi-aspect Preferences and Intents for Multi-behavioral Sequential Recommendation—0
Modeling Sequences as Star Graphs to Address Over-smoothing in Self-attentive Sequential Recommendation—0
Modeling Temporal Positive and Negative Excitation for Sequential Recommendation—0
Future Data Helps Training: Modeling Future Contexts for Session-based Recommendation—0
MOI-Mixer: Improving MLP-Mixer with Multi Order Interactions in Sequential Recommendation—0
Molar: Multimodal LLMs with Collaborative Filtering Alignment for Enhanced Sequential Recommendation—0
AdaptiveRec: Adaptively Construct Pairs for Contrastive Learning in Sequential Recommendation—0
Multi-intent Aware Contrastive Learning for Sequential Recommendation—0
Multi-level Contrastive Learning Framework for Sequential Recommendation—0
Multimodal Difference Learning for Sequential Recommendation—0
Multimodal Point-of-Interest Recommendation—0
Multimodal Pre-training Framework for Sequential Recommendation via Contrastive Learning—0
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