推荐系统作为深度学习御三家（CV, NLP, RS）之一，一直都是学术界和工业界的热门研究topic。为了更加清楚的掌握推荐系统的前沿方向与最新进展，本文整理了最近一年顶会中推荐系统相关的论文，一共涵盖SIGIR2020, KDD2020, RecSys2020, CIKM2020, AAAI2021, WSDM2021, WWW2021七个会议共221篇论文。本次整理以long paper和research paper为主，也包含少量的short paper和industry paper。

本文按照个人阅读习惯和文章的侧重点将这些论文分为以下五大类和若干小类：

1 推荐任务

  • Collaborative Filtering

  • Sequential/Session-based Recommendations

  • Knowledge-aware Recommendations

  • Feature Interactions

  • Conversational Recommender System

  • Social Recommendations

  • News Recommendations

  • Text-aware Recommendations

  • Point-of-Interest

  • Online Recommendations

  • Group Recommendations

  • Multi-task/Multi-behavior/Cross-domain Recommendations

  • Other Task

2 推荐的热门研究话题

  • Debias in Recommender System

  • Fairness in Recommender System

  • Attack in Recommender System

  • Explanation in Recommender System

  • Long-tail/Cold-start in Recommender System

  • Evaluation

3 先进技术在推荐中的应用

  • Pre-training in Recommender System

  • Reinforcement Learning in Recommender System

  • Knowledge Distillation in Recommender System

  • NAS in Recommender System

  • Federated Learning in Recommender System

4 理论/实验分析

5 其他

GitHub地址：https://github.com/RUCAIBox/Awesome-RSPapers

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