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Sequential Recommendation

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평가표: 13
보존된 평가 기록: 20

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.

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/tingjshen/urllm

공식 코드

Exploring User Retrieval Integration towards Large Language Models for Cross-Domain Sequential Recommendation

https://github.com/tokkiu/ecl

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Equivariant Contrastive Learning for Sequential Recommendation

https://github.com/tsinghua-fib-lab/dcn

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Mutual Harmony: Sequential Recommendation with Dual Contrastive Network

https://github.com/tsinghua-fib-lab/recsys2023-sine

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Understanding and Modeling Passive-Negative Feedback for Short-video Sequential Recommendation

https://github.com/tsinghua-fib-lab/sigir24-frec

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Modeling User Fatigue for Sequential Recommendation

https://github.com/tsinghua-fib-lab/www2023-dfar

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Dual-interest Factorization-heads Attention for Sequential Recommendation

https://github.com/ufnrec-code/ufnrec

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UFNRec: Utilizing False Negative Samples for Sequential Recommendation

https://github.com/uikdwnd/FENRec

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Future Sight and Tough Fights: Revolutionizing Sequential Recommendation with FENRec

https://github.com/unintelligentmumu/matrrec

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MaTrRec: Uniting Mamba and Transformer for Sequential Recommendation

https://github.com/urielsinger/trans2d

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Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce

https://github.com/ustc-starteam/dr4sr

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Dataset Regeneration for Sequential Recommendation

https://github.com/ustc-starteam/td3

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TD3: Tucker Decomposition Based Dataset Distillation Method for Sequential Recommendation

https://github.com/ustcagi/dv-fsr

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DV-FSR: A Dual-View Target Attack Framework for Federated Sequential Recommendation

https://github.com/vasily789/symmetry-structured-convolutional-neural-networks

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Symmetry Structured Convolutional Neural Networks

https://github.com/vinairesearch/recgpt

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RecGPT: Generative Pre-training for Text-based Recommendation

https://github.com/waldenlqy/sam

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Sparse Attentive Memory Network for Click-through Rate Prediction with Long Sequences

https://github.com/wangjiachun0426/StackRec

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StackRec: Efficient Training of Very Deep Sequential Recommender Models by Iterative Stacking

https://github.com/wangjlgz/MetaTL

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Sequential Recommendation for Cold-start Users with Meta Transitional Learning

https://github.com/weizhangltt/dual-recommend

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Learning Dual Dynamic Representations on Time-Sliced User-Item Interaction Graphs for Sequential Recommendation

https://github.com/whuir/diffurec

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DiffuRec: A Diffusion Model for Sequential Recommendation

https://github.com/whuir/mgnm

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When Multi-Level Meets Multi-Interest: A Multi-Grained Neural Model for Sequential Recommendation

https://github.com/williamliujl/llmrec

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LLMRec: Benchmarking Large Language Models on Recommendation Task

https://github.com/wujiangxu/amid

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Rethinking Cross-Domain Sequential Recommendation under Open-World Assumptions

https://github.com/wujiangxu/macd

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Towards Open-world Cross-Domain Sequential Recommendation: A Model-Agnostic Contrastive Denoising Approach

https://github.com/wujiangxu/slmrec

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SLMRec: Distilling Large Language Models into Small for Sequential Recommendation

https://github.com/wuliwei9278/SQL-Rank

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Advances in Collaborative Filtering and Ranking

https://github.com/wyd0042/EchoMamba4Rec

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EchoMamba4Rec: Harmonizing Bidirectional State Space Models with Spectral Filtering for Advanced Sequential Recommendation

https://github.com/wyqing20/aprec

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Attacking Pre-trained Recommendation

https://github.com/wyqing20/pfrec

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Selective Fairness in Recommendation via Prompts

https://github.com/wzf2000/macrec

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MACRec: a Multi-Agent Collaboration Framework for Recommendation

https://github.com/xjaw/s4rec

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Leave No One Behind: Online Self-Supervised Self-Distillation for Sequential Recommendation

https://github.com/xlx0010/hgnn

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Factorial User Modeling with Hierarchical Graph Neural Network for Enhanced Sequential Recommendation

https://github.com/xuchen0427/dually-enhanced-propensity-score-estimation-in-sequential-recommendation

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Dually Enhanced Propensity Score Estimation in Sequential Recommendation

https://github.com/xyliugo/odmt

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Online Distillation-enhanced Multi-modal Transformer for Sequential Recommendation

https://github.com/yangyongjin/melo

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Meta-Learning with Adaptive Weighted Loss for Imbalanced Cold-Start Recommendation

https://github.com/yangzhengyi98/dreamrec

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Generate What You Prefer: Reshaping Sequential Recommendation via Guided Diffusion

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