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README.md

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# 推荐系统相关论文汇总
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([English Version is Here](/README_EN.md))
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## 介绍
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1. 截至2023-08-18,本仓库收集汇总了推荐系统领域相关论文共**719**篇,涉及:**召回****粗排****精排****重排****多任务****多场景****多模态****冷启动****校准**
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1. 截至2023-08-20,本仓库收集汇总了推荐系统领域相关论文共**720**篇,涉及:**召回****粗排****精排****重排****多任务****多场景****多模态****冷启动****校准**
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**纠偏****多样性****公平性****反馈延迟****蒸馏****对比学习****因果推断****Look-Alike****Learning-to-Rank****强化学习**等领域,本仓库会跟踪业界进展,持续更新。
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2. 因文件名特殊字符的限制,故论文title中所有的`:`都改为了`-`,检索时请注意。
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3. 文件名前缀中带有`[]`的,表明本人已经通读过,第一个`[]`中为论文年份,第二个`[]`中为发表机构或公司(可选),第三个`[]`中为论文提出的model或method的简称(可选)。
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- [Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction](Industry/Deep%20Spatio-Temporal%20Neural%20Networks%20for%20Click-Through%20Rate%20Prediction.pdf)
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- [Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback](Industry/Denoising%20Neural%20Network%20for%20News%20Recommendation%20with%20Positive%20and%20Negative%20Implicit%20Feedback.pdf)
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- [Denoising User-aware Memory Network for Recommendation](Industry/Denoising%20User-aware%20Memory%20Network%20for%20Recommendation.pdf)
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- [Deep Context Interest Network for Click-Through Rate Prediction](Industry/Deep%20Context%20Interest%20Network%20for%20Click-Through%20Rate%20Prediction.pdf)
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- [Disentangling Long and Short-Term Interests for Recommendation](Industry/Disentangling%20Long%20and%20Short-Term%20Interests%20for%20Recommendation.pdf)
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- [Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)](Industry/Empowering%20Long-tail%20Item%20Recommendation%20through%20Cross%20Decoupling%20Network%20%28CDN%29.pdf)
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- [E-Commerce Item Recommendation Based on Field-aware Factorization Machine](Industry/E-Commerce%20Item%20Recommendation%20Based%20on%20Field-aware%20Factorization%20Machine.pdf)

README_EN.md

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# Summary of Papers Related to Recommendation System
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## Introduce
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1. Up to 2023-08-18, **719** papers related to recommendation system have been collected and summarized in this repo,
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1. Up to 2023-08-20, **720** papers related to recommendation system have been collected and summarized in this repo,
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including: **Match**, **Pre-Rank**, **Rank**, **Re-Rank**, **Multi-Task**, **Multi-Scenario**, **Multi-Modal**, **Cold-Start**, **Calibration**,
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**Debias**, **Diversity**, **Fairness**, **Feedback-Delay**, **Distillation**, **Contrastive Learning**, **Casual Inference**,
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**Look-Alike**, **Learning-to-Rank**, **Reinforcement Learning** and other fields, the repo will track the industry progress and update continuely.
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- [Deep Spatio-Temporal Neural Networks for Click-Through Rate Prediction](Industry/Deep%20Spatio-Temporal%20Neural%20Networks%20for%20Click-Through%20Rate%20Prediction.pdf)
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- [Denoising Neural Network for News Recommendation with Positive and Negative Implicit Feedback](Industry/Denoising%20Neural%20Network%20for%20News%20Recommendation%20with%20Positive%20and%20Negative%20Implicit%20Feedback.pdf)
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- [Denoising User-aware Memory Network for Recommendation](Industry/Denoising%20User-aware%20Memory%20Network%20for%20Recommendation.pdf)
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- [Deep Context Interest Network for Click-Through Rate Prediction](Industry/Deep%20Context%20Interest%20Network%20for%20Click-Through%20Rate%20Prediction.pdf)
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- [Disentangling Long and Short-Term Interests for Recommendation](Industry/Disentangling%20Long%20and%20Short-Term%20Interests%20for%20Recommendation.pdf)
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- [Empowering Long-tail Item Recommendation through Cross Decoupling Network (CDN)](Industry/Empowering%20Long-tail%20Item%20Recommendation%20through%20Cross%20Decoupling%20Network%20%28CDN%29.pdf)
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- [E-Commerce Item Recommendation Based on Field-aware Factorization Machine](Industry/E-Commerce%20Item%20Recommendation%20Based%20on%20Field-aware%20Factorization%20Machine.pdf)

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