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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 201–225 of 554 papers

TitleStatusHype
Inter-sequence Enhanced Framework for Personalized Sequential Recommendation—0
Counterfactual Learning-Driven Representation Disentanglement for Search-Enhanced Recommendation—0
Semantic Codebook Learning for Dynamic Recommendation Models—0
Invariant representation learning for sequential recommendation—0
GENET: Unleashing the Power of Side Information for Recommendation via Hypergraph Pre-training—0
Generative Sequential Recommendation with GPTRec—0
Intent-Enhanced Data Augmentation for Sequential Recommendation—0
LARES: Latent Reasoning for Sequential Recommendation—0
CoST: Contrastive Quantization based Semantic Tokenization for Generative Recommendation—0
Generate and Instantiate What You Prefer: Text-Guided Diffusion for Sequential Recommendation—0
Attention-based sequential recommendation system using multimodal data—0
Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement—0
Fusing Similarity Models with Markov Chains for Sparse Sequential Recommendation—0
Freudian and Newtonian Recurrent Cell for Sequential Recommendation—0
A Framework for Elastic Adaptation of User Multiple Intents in Sequential Recommendation—0
Fisher-Weighted Merge of Contrastive Learning Models in Sequential Recommendation—0
A Systematic Replicability and Comparative Study of BSARec and SASRec for Sequential Recommendation—0
Filtering with Time-frequency Analysis: An Adaptive and Lightweight Model for Sequential Recommender Systems Based on Discrete Wavelet Transform—0
Few-shot Model Extraction Attacks against Sequential Recommender Systems—0
Integrating Offline Reinforcement Learning with Transformers for Sequential Recommendation—0
Generating Negative Samples for Sequential Recommendation—0
Generative Diffusion Models for Sequential Recommendations—0
FELLAS: Enhancing Federated Sequential Recommendation with LLM as External Services—0
Federated Mixture-of-Expert for Non-Overlapped Cross-Domain Sequential Recommendation—0
Context-based Fast Recommendation Strategy for Long User Behavior Sequence in Meituan Waimai—0
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