IJCAI_2022_recommendation_papers.md

Catalog (目录)

1 Sort by task (按照任务场景划分)

• POI
• Sequential/Session-based Recommendation

2 Sort by main technique (按照主要技术划分)

• Federated Learning based
• Graph Neural Network

3 Sort by topic (按研究话题划分)

• Bias/Debias in Recommender System

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Sort by task(按照任务场景划分)

POI

• Modeling Spatio-temporal Neighbourhood for Personalized Point-of-interest Recommendation. IJCAI 2022 [融入知识图谱和时域信息，实现个性化POI推荐]

• Next Point-of-Interest Recommendation with Inferring Multi-step Future Preferences.IJCAI 2022 [考虑用户未来偏好]

Sequential/Session-based Recommendation

• MLP4Rec: A Pure MLP Architecture for Sequential Recommendations. IJCAI 2022 [利用MLP捕捉商品特征中的序列关系]

• Enhancing Sequential Recommendation with Graph Contrastive Learning. IJCAI 2022 [用于序列推荐的图对比学习]

Sort by main technique (按照主要技术划分)

Federated Learning based

• Poisoning Deep Learning based Recommender Model in Federated Learning Scenarios. IJCAI 2022 [设计针对基于深度学习的推荐模型的攻击]

Graph Neural Network

• Heterogeneous Interactive Snapshot Network for Review-Enhanced Stock Profiling and Recommendation. IJCAI 2022

• Self-supervised Graph Neural Networks for Multi-behavior Recommendation. IJCAI 2022 [GNN + 多行为推荐]

• RecipeRec: A Heterogeneous Graph Learning Model for Recipe Recommendation. IJCAI 2022 [用于食谱推荐的新型异构图学习模型]

Sort by topic (按研究话题划分)

Bias/Debias in Recommender System

• Trading Hard Negatives and True Negatives: A Debiased Contrastive Collaborative Filtering Approach. IJCAI 2022 [探索正确的负样本]

• Towards Resolving Propensity Contradiction in Offline Recommender Learning. IJCAI 2022 [倾向无关的泛化误差边界，并通过对抗学习最小化理论边界]