推荐系统作为AI最成功和最重要的应用之一，帮助消费者更容易地找到相关的或感兴趣的内容、商品或者服务。
对于想学习推荐系统的同学，我整理了WSDM2022最新的包括了序列推荐、跨域推荐、去偏推荐、联邦推荐等13篇推荐系统论文，供大家提前领略学术前沿趋势与牛人的最新想法。
01.RecGURU: Adversarial Learning of Generalized User Representations for Cross-Domain Recommendation02.Personalized Transfer of User Preferences for Cross-domain Recommendation03.Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation04.Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation05.It Is Different When Items Are Older: Debiasing Recommendations When Selection Bias and User Preferences are Dynamic06.Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning07.PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion08.Profiling the Design Space for Graph Neural Networks based Collaborative Filtering09.Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation10.Enumerating Fair Packages for Group Recommendations11.Long Short-Term Temporal Meta-learning in Online Recommendation12.A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising13.Choosing the Best of All Worlds: Accurate, Diverse, and Novel Recommendations through Multi-Objective Reinforcement Learning那么多推荐论文，需要怎么去精读和泛读呢，能让你对推荐系统中的各个部分的算法有一个总体的认识，我推荐你来听Pirtuo老师的《欢迎来到推荐的世界》直播课。—— 老师介绍 ——
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7月21日 晚上20：00
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7月22日 晚上20：00
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已预约的同学，还额外附赠2022推荐系统paper13篇~
