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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 191200 of 554 papers

TitleStatusHype
DA-GCN: A Domain-aware Attentive Graph Convolution Network for Shared-account Cross-domain Sequential Recommendation0
DACSR: Decoupled-Aggregated End-to-End Calibrated Sequential Recommendation0
Autoregressive Generation Strategies for Top-K Sequential Recommendations0
ID-centric Pre-training for Recommendation0
Intelligent Model Update Strategy for Sequential Recommendation0
Automated Prompting for Non-overlapping Cross-domain Sequential Recommendation0
CSRN: Collaborative Sequential Recommendation Networks for News Retrieval0
HMamba: Hyperbolic Mamba for Sequential Recommendation0
Cross-Domain Sequential Recommendation via Neural Process0
An Analysis of Approaches Taken in the ACM RecSys Challenge 2018 for Automatic Music Playlist Continuation0
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