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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/chr26195/caseq

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Towards Out-of-Distribution Sequential Event Prediction: A Causal Treatment

https://github.com/cjx96/c2dsr

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Contrastive Cross-Domain Sequential Recommendation

https://github.com/cloudcatcher888/rcl

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Relative Contrastive Learning for Sequential Recommendation with Similarity-based Positive Pair Selection

https://github.com/col-tasas/2025-oco-with-iqcs

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CROSSAN: Towards Efficient and Effective Adaptation of Multiple Multimodal Foundation Models for Sequential Recommendation

https://github.com/cpark88/CGRec

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Cracking the Code of Negative Transfer: A Cooperative Game Theoretic Approach for Cross-Domain Sequential Recommendation

https://github.com/cpark88/syncrec

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Pacer and Runner: Cooperative Learning Framework between Single- and Cross-Domain Sequential Recommendation

https://github.com/crowddynamicslab/preprec

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A Pre-trained Sequential Recommendation Framework: Popularity Dynamics for Zero-shot Transfer

https://github.com/ct4rec/ct4rec

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CT4Rec: Simple yet Effective Consistency Training for Sequential Recommendation

https://github.com/cuiqiang1990/HCA

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A Hierarchical Contextual Attention-based GRU Network for Sequential Recommendation

https://github.com/cuiqiang1990/MV-RNN

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MV-RNN: A Multi-View Recurrent Neural Network for Sequential Recommendation

https://github.com/dbis-uibk/gcnext

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Unsupervised Graph Embeddings for Session-based Recommendation with Item Features

https://github.com/deezer/recsys24-pisa

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Transformers Meet ACT-R: Repeat-Aware and Sequential Listening Session Recommendation

https://github.com/deezer/sigir23-mojito

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Attention Mixtures for Time-Aware Sequential Recommendation

https://github.com/demoleiwang/ec4srec

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Explanation Guided Contrastive Learning for Sequential Recommendation

https://github.com/demoleiwang/llmsrec_syn

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The Whole is Better than the Sum: Using Aggregated Demonstrations in In-Context Learning for Sequential Recommendation

https://github.com/dh-r/llm-sequential-recommendation

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Leveraging Large Language Models for Sequential Recommendation

https://github.com/dimarziobian/abxi

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ABXI: Invariant Interest Adaptation for Task-Guided Cross-Domain Sequential Recommendation

https://github.com/dimarziobian/cpmr

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CPMR: Context-Aware Incremental Sequential Recommendation with Pseudo-Multi-Task Learning

https://github.com/dmhyun/PERIS

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Beyond Learning from Next Item: Sequential Recommendation via Personalized Interest Sustainability

https://github.com/dmirlab-group/tea

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TEA: A Sequential Recommendation Framework via Temporally Evolving Aggregations

https://github.com/drhuangliwei/PTGCN

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Position-enhanced and Time-aware Graph Convolutional Network for Sequential Recommendations

https://github.com/dygrec/tgsrec

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Continuous-Time Sequential Recommendation with Temporal Graph Collaborative Transformer

https://github.com/ehgh/parsrec

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PARSRec: Explainable Personalized Attention-fused Recurrent Sequential Recommendation Using Session Partial Actions

https://github.com/ethan00si/sesrec-sigir-2023

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When Search Meets Recommendation: Learning Disentangled Search Representation for Recommendation

https://github.com/fairymeng/trustsr

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TruthSR: Trustworthy Sequential Recommender Systems via User-generated Multimodal Content

https://github.com/fengliu-1/fmrec

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Flow Matching based Sequential Recommender Model

https://github.com/floatsdsds/gnno

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Neighborhood-based Hard Negative Mining for Sequential Recommendation

https://github.com/furyton/csrec

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Learning Robust Sequential Recommenders through Confident Soft Labels

https://github.com/fuxiailab/rl4rs

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RL4RS: A Real-World Dataset for Reinforcement Learning based Recommender System

https://github.com/gair-lab/iisan

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IISAN: Efficiently Adapting Multimodal Representation for Sequential Recommendation with Decoupled PEFT

https://github.com/gayan225/symmetry-structured-convolutional-neural-networks

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Symmetry Structured Convolutional Neural Networks

https://github.com/gimpong/MM23-MISSRec

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MISSRec: Pre-training and Transferring Multi-modal Interest-aware Sequence Representation for Recommendation

https://github.com/gnimixy/lancer

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Reformulating Sequential Recommendation: Learning Dynamic User Interest with Content-enriched Language Modeling

https://github.com/graph-team/apgl4sr

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APGL4SR: A Generic Framework with Adaptive and Personalized Global Collaborative Information in Sequential Recommendation

https://github.com/gtshs2/HCRNN

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Hierarchical Context enabled Recurrent Neural Network for Recommendation

https://github.com/guanyu-lin/man

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Mixed Attention Network for Cross-domain Sequential Recommendation

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