https://github.com/shenweichen/DeepCTR
DeepRec: An Open-source Toolkit for Deep Learning based Recommendation
Papers with Code 아카이브
Sequential Recommendation
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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/shenweichen/DeepCTR-Torch
DeepRec: An Open-source Toolkit for Deep Learning based Recommendation
https://github.com/shenweichen/deepmatch
DeepRec: An Open-source Toolkit for Deep Learning based Recommendation
https://github.com/shuchenliu/assignment2
CosRec: 2D Convolutional Neural Networks for Sequential Recommendation
https://github.com/tsinghua-fib-lab/SIGIR21-SURGE
https://github.com/tunghia1890/BERT4Rec_TF2x
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
https://github.com/vatsalsaglani/bert4rec
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
https://github.com/wenyueh/llm-recsys-id
https://github.com/woeee/fmlp-rec
Filter-enhanced MLP is All You Need for Sequential Recommendation
https://github.com/wuliwei9278/HGN_baseline
https://github.com/xiaominglalala/Session_based_Recommendation
Topic-Enhanced Memory Networks for Personalised Point-of-Interest Recommendation
https://github.com/xinyooo/ALBERT4Rec
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
https://github.com/yehjin-shin/bsarec
An Attentive Inductive Bias for Sequential Recommendation beyond the Self-Attention
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.