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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
Facet-Aware Multi-Head Mixture-of-Experts Model for Sequential Recommendation—0
FairSR: Fairness-aware Sequential Recommendation through Multi-Task Learning with Preference Graph Embeddings—0
Farzi Data: Autoregressive Data Distillation—0
SC-Rec: Enhancing Generative Retrieval with Self-Consistent Reranking for Sequential Recommendation—0
Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation—0
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services—0
Few-shot Model Extraction Attacks against Sequential Recommender Systems—0
Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach—0
Filtering with Time-frequency Analysis: An Adaptive and Lightweight Model for Sequential Recommender Systems Based on Discrete Wavelet Transform—0
Self-supervised Learning for Sequential Recommendation with Model Augmentation—0
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation—0
Towards Efficient and Effective Adaptation of Large Language Models for Sequential Recommendation—0
Self-Supervised Reinforcement Learning for Recommender Systems—0
Freudian and Newtonian Recurrent Cell for Sequential Recommendation—0
Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation—0
Generate and Instantiate What You Prefer: Text-Guided Diffusion for Sequential Recommendation—0
Generating Negative Samples for Sequential Recommendation—0
Generative Diffusion Models for Sequential Recommendations—0
Generative Sequential Recommendation with GPTRec—0
GENET: Unleashing the Power of Side Information for Recommendation via Hypergraph Pre-training—0
GIMIRec: Global Interaction Information Aware Multi-Interest Framework for Sequential Recommendation—0
GLINT-RU: Gated Lightweight Intelligent Recurrent Units for Sequential Recommender Systems—0
Semantic Retrieval Augmented Contrastive Learning for Sequential Recommendation—0
GOT4Rec: Graph of Thoughts for Sequential Recommendation—0
SEMINAR: Search Enhanced Multi-modal Interest Network and Approximate Retrieval for Lifelong Sequential Recommendation—0
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