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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

Showing 381390 of 554 papers

TitleStatusHype
Cold-start Sequential Recommendation via Meta Learner0
RecGPT: Generative Personalized Prompts for Sequential Recommendation via ChatGPT Training Paradigm0
Collective Mobile Sequential Recommendation: A Recommender System for Multiple Taxicabs0
Conditional Denoising Diffusion for Sequential Recommendation0
Confidence-aware Fine-tuning of Sequential Recommendation Systems via Conformal Prediction0
Context-aware Sequential Recommendation0
Context-based Fast Recommendation Strategy for Long User Behavior Sequence in Meituan Waimai0
Think Before Recommend: Unleashing the Latent Reasoning Power for Sequential Recommendation0
Contrastive Learning Method for Sequential Recommendation based on Multi-Intention Disentanglement0
RecMind: Large Language Model Powered Agent For Recommendation0
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