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DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network


Aug 22, 2021
Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He

* CIKM2021 

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Causal Incremental Graph Convolution for Recommender System Retraining


Aug 16, 2021
Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Jun Shi, Yongdong Zhang

* submitted to TNNLS 

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Time-aware Path Reasoning on Knowledge Graph for Recommendation


Aug 05, 2021
Yuyue Zhao, Xiang Wang, Jiawei Chen, Wei Tang, Yashen Wang, Xiangnan He, Haiyong Xie

* 22 pages, ACM Transactions on Information Systems (TOIS) Under Review 

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Exploring Lottery Ticket Hypothesis in Media Recommender Systems


Aug 02, 2021
Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu, Xiangnan He


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User-specific Adaptive Fine-tuning for Cross-domain Recommendations


Jun 18, 2021
Lei Chen, Fajie Yuan, Jiaxi Yang, Xiangnan He, Chengming Li, Min Yang


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Empowering Language Understanding with Counterfactual Reasoning


Jun 06, 2021
Fuli Feng, Jizhi Zhang, Xiangnan He, Hanwang Zhang, Tat-Seng Chua

* Accepted by Findings of ACL'21 

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Deconfounded Recommendation for Alleviating Bias Amplification


May 22, 2021
Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang, Tat-Seng Chua

* Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discoveryand Data Mining (KDD 2021) 

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Probabilistic and Variational Recommendation Denoising


May 20, 2021
Yu Wang, Xin Xin, Zaiqiao Meng, Xiangnan He, Joemon Jose, Fuli Feng

* 13 pages, 17 figures 

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Graph Learning based Recommender Systems: A Review


May 13, 2021
Shoujin Wang, Liang Hu, Yan Wang, Xiangnan He, Quan Z. Sheng, Mehmet A. Orgun, Longbing Cao, Francesco Ricci, Philip S. Yu

* Accepted by IJCAI 2021 Survey Track, copyright is owned to IJCAI. The first systematic survey on graph learning based recommender systems. arXiv admin note: text overlap with arXiv:2004.11718 

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Causal Intervention for Leveraging Popularity Bias in Recommendation


May 13, 2021
Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling, Yongdong Zhang

* Appear in SIGIR 2021 

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AutoDebias: Learning to Debias for Recommendation


May 10, 2021
Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin, Keping Yang

* Accepted by SIGIR 2021 

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A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation


Apr 27, 2021
Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang

* In submission 

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Structure-Enhanced Meta-Learning For Few-Shot Graph Classification


Mar 11, 2021
Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li, Xiangnan He

* Submitted to AI Open 

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Learning Intents behind Interactions with Knowledge Graph for Recommendation


Feb 14, 2021
Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He, Tat-Seng Chua

* WWW 2021 oral presentation 

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Advances and Challenges in Conversational Recommender Systems: A Survey


Feb 07, 2021
Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke, Tat-Seng Chua

* 30 pages, 8 figures 

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On the Equivalence of Decoupled Graph Convolution Network and Label Propagation


Oct 23, 2020
Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding, Peng Cui


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Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method


Oct 22, 2020
Fuli Feng, Weiran Huang, Xin Xin, Xiangnan He, Tat-Seng Chua


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Self-supervised Graph Learning for Recommendation


Oct 21, 2020
Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian, Xing Xie

* 11 pages, 7 pages, 5 tables 

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CatGCN: Graph Convolutional Networks with Categorical Node Features


Sep 17, 2020
Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling, Yongdong Zhang


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Adversarial Attack on Large Scale Graph


Sep 08, 2020
Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He, Zibin Zheng

* In submission to Journal, the codes are availiable at https://github.com/EdisonLeeeee/GraphAdv 

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A Survey on Large-scale Machine Learning


Aug 10, 2020
Meng Wang, Weijie Fu, Xiangnan He, Shijie Hao, Xindong Wu


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Disentangled Graph Collaborative Filtering


Jul 03, 2020
Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu, Tat-Seng Chua

* SIGIR 2020 

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Data Augmentation View on Graph Convolutional Network and the Proposal of Monte Carlo Graph Learning


Jun 23, 2020
Hande Dong, Zhaolin Ding, Xiangnan He, Fuli Feng, Shuxian Bi


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Modeling Personalized Item Frequency Information for Next-basket Recommendation


May 31, 2020
Haoji Hu, Xiangnan He, Jinyang Gao, Zhi-Li Zhang


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