https://github.com/wzhe06/Reco-papers

Classic papers and resources on recommendation
https://github.com/wzhe06/Reco-papers

deep-learning exploration-exploitation machine-learning recommendation recommender-system reinforcement-learning

Last synced: 12 months ago
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Classic papers and resources on recommendation

• Host: GitHub
• URL: https://github.com/wzhe06/Reco-papers
• Owner: wzhe06
• License: mit
• Created: 2018-05-29T17:29:04.000Z (almost 8 years ago)
• Default Branch: master
• Last Pushed: 2020-06-13T14:54:40.000Z (almost 6 years ago)
• Last Synced: 2024-11-11T23:38:05.157Z (over 1 year ago)
• Topics: deep-learning, exploration-exploitation, machine-learning, recommendation, recommender-system, reinforcement-learning
• Language: Python
• Homepage: https://github.com/wzhe06/Reco-papers
• Size: 169 MB
• Stars: 3,314
• Watchers: 194
• Forks: 804
• Open Issues: 2
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

• awesome-list - wzhe06/Reco-papers - Classic papers and resources on recommendation (Machine Learning / JavaScript)
• StarryDivineSky - wzhe06/Reco-papers - 2023）和研究方向（如协同过滤、深度学习、多模态推荐）双重维度分类，每个条目均标注论文发表年份、核心贡献、关键技术点及代表性代码链接，便于快速定位研究进展。项目特别强调实践价值，提供基于PyTorch、TensorFlow等框架的代码实现案例，以及Kaggle竞赛数据集和工业级推荐系统架构分析。工作原理采用分层结构设计：基础层包含经典论文（如ItemCF、SVD、Wide&Deep）；进阶层涵盖深度学习模型（如NeuMF、GraphSAGE）；前沿层聚焦最新研究（如Self-Attention、多模态融合）。所有内容均附中文翻译与技术解析，适合不同层次研究者从理论学习到工程实践的全流程参考。项目持续更新维护，已收录超过300篇论文和50个开源项目，是学习推荐系统领域知识的权威资源库。 (推荐系统算法库与列表 / 资源传输下载)