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Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and
  Method

Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method

19 August 2024
Chen Yang
Sunhao Dai
Yupeng Hou
Wayne Xin Zhao
Jun Xu
Yang Song
Hengshu Zhu
ArXiv (abs)PDFHTMLGithub

Papers citing "Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method"

5 / 5 papers shown
Title
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Shiyin Tan
Dongyuan Li
Renhe Jiang
Zhen Wang
Xingtong Yu
Manabu Okumura
CML
153
0
0
20 May 2025
S^3-Rec: Self-Supervised Learning for Sequential Recommendation with
  Mutual Information Maximization
S^3-Rec: Self-Supervised Learning for Sequential Recommendation with Mutual Information Maximization
Kun Zhou
Haibo Wang
Wayne Xin Zhao
Yutao Zhu
Sirui Wang
Fuzheng Zhang
Zhongyuan Wang
Ji-Rong Wen
136
820
0
18 Aug 2020
LightGCN: Simplifying and Powering Graph Convolution Network for
  Recommendation
LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation
Xiangnan He
Kuan Deng
Xiang Wang
Yan Li
Yongdong Zhang
Meng Wang
GNN
189
3,674
0
06 Feb 2020
A Survey on Causal Inference
A Survey on Causal Inference
Liuyi Yao
Zhixuan Chu
Sheng Li
Yaliang Li
Jing Gao
Aidong Zhang
CML
100
510
0
05 Feb 2020
Recommendations as Treatments: Debiasing Learning and Evaluation
Recommendations as Treatments: Debiasing Learning and Evaluation
Tobias Schnabel
Adith Swaminathan
Ashudeep Singh
Navin Chandak
Thorsten Joachims
CML
162
686
0
17 Feb 2016
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