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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 251–275 of 554 papers

TitleStatusHype
LLM-based User Profile Management for Recommender System—0
A Survey on Multi-Behavior Sequential Recommendation—0
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation—0
Improving LLM Interpretability and Performance via Guided Embedding Refinement for Sequential Recommendation—0
Enhancing Transformers without Self-supervised Learning: A Loss Landscape Perspective in Sequential Recommendation—0
LLM-based Bi-level Multi-interest Learning Framework for Sequential Recommendation—0
LLM is Knowledge Graph Reasoner: LLM's Intuition-aware Knowledge Graph Reasoning for Cold-start Sequential Recommendation—0
LLMSeR: Enhancing Sequential Recommendation via LLM-based Data Augmentation—0
Model-enhanced Contrastive Reinforcement Learning for Sequential Recommendation—0
Enhancing Sequential Recommendation with Graph Contrastive Learning—0
Cold-start Sequential Recommendation via Meta Learner—0
Enhancing CTR Prediction through Sequential Recommendation Pre-training: Introducing the SRP4CTR Framework—0
Coarse-to-Fine Sparse Sequential Recommendation—0
END4Rec: Efficient Noise-Decoupling for Multi-Behavior Sequential Recommendation—0
ClusterSeq: Enhancing Sequential Recommender Systems with Clustering based Meta-Learning—0
CITIES: Contextual Inference of Tail-Item Embeddings for Sequential Recommendation—0
ELASTIC: Efficient Linear Attention for Sequential Interest Compression—0
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning—0
CauseRec: Counterfactual User Sequence Synthesis for Sequential Recommendation—0
Efficient Inference of Sub-Item Id-based Sequential Recommendation Models with Millions of Items—0
Are We Really Achieving Better Beyond-Accuracy Performance in Next Basket Recommendation?—0
A Case Study on Sampling Strategies for Evaluating Neural Sequential Item Recommendation Models—0
Efficient and Effective Adaptation of Multimodal Foundation Models in Sequential Recommendation—0
Cascading: Association Augmented Sequential Recommendation—0
A Review-Driven Neural Model for Sequential Recommendation—0
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