Conference papers：
In the year of 2022:
[1] Interpolative Distillation for Unifying Biased and Debiased Recommendation , Sihao Ding, Fuli Feng, Xiangnan He, Jinqiu Jin, Wenjie Wang, Yong Liao & Yongdong Zhang, SIGIR 2022 (Full, Accept rate: 20%). PDF
[2] Group Contextualization for Video Recognition , Yanbin Hao, Hao Zhang, Chong-Wah Ngo & Xiangnan He, CVPR 2022 (Full, Accept rate: 25.3%). PDF
[3] Discovering Invariant Rationales for Graph Neural Networks , Ying-Xin Wu, Xiang Wang, An Zhang, Xiangnan He & Tat-Seng Chua, ICLR 2022. PDF
[4] Cross Pairwise Ranking for Unbiased Item Recommendation , Qi Wan, Xiangnan He, Xiang Wang, Jiancan Wu, Wei Guo & Ruiming Tang, WWW 2022 (Full, Accept rate: 17.7%). PDF
[5] Learning Robust Recommenders through Cross-Model Agreement , Yu Wang, Xin Xin, Zaiqiao Meng, Jeoman Jose, Fuli Feng & Xiangnan He, WWW 2022 (Full, Accept rate: 17.7%). PDF
[6] Interactive Hypergraph Neural Network for Personalized Product Search , Dian Cheng, Jiawei Chen, Wenjun Peng, Wenqin Ye, Fuyu Lv, Tao Zhuang, Xiaoyi Zeng & Xiangnan He, WWW 2022 (Full, Accept rate: 17.7%). PDF
[7] Time-aware Path Reasoning on Knowledge Graph for Recommendation , Yuyue Zhao, Xiang Wang, Jiawei Chen, Wei Tang, Yashen Wang, Xiangnan He & Haiyong Xie, ACM Transactions on Information Systems, TOIS 2022. PDF
[8] Causal Incremental Graph Convolution for Recommender System Retraining , Sihao Ding, Fuli Feng, Xiangnan He, Yong Liao, Jun Shi & Yongdong Zhang, IEEE Transactions on Neural Networks and Learning Systems , TNNLS 2022. PDF
[9] GDSRec: Graph-Based Decentralized Collaborative Filtering for Social Recommendation , Jiajia Chen, Xin Xin, Xianfeng Liang, Xiangnan He & Jun Liu, IEEE Transactions on Knowledge and Data Engineering, TKDE 2022. PDF
[10] CatGCN: Graph Convolutional Networks with Categorical Node Features , Weijian Chen, Fuli Feng, Qifan Wang, Xiangnan He, Chonggang Song, Guohui Ling & Yongdong Zhang, IEEE Transactions on Knowledge and Data Engineering, TKDE 2022. PDF
[11] Exploring Lottery Ticket Hypothesis in Media Recommender Systems, Yanfang Wang, Yongduo Sui, Xiang Wang, Zhenguang Liu & Xiangnan He, International Journal of Intelligent Systems, IJIS 2022. PDF
[12] Graph Convolution Machine for Context-aware Recommender System, Jiancan Wu, Xiangnan He*, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian & Xing Xie, Frontiers of Computer Science, FOCS 2022. PDF
[13] Attention in Attention: Modeling Context Correlation for Efficient Video Classification , Yanbin Hao, Shuo Wang, Pei Cao, Xinjian Gao, Tong Xu, Jinmeng Wu, Xiangnan He, TCSVT 2022. PDF
[14] Boosting Hyperspectral Image Classification with Dual Hierarchical Learning, Shuo Wang, Huixia Ben, Yanbin Hao, Xiangnan He, Meng Wang, TOMM 2022. PDF
[15] Multi-directional Knowledge Transfer for Few-Shot Learning, Shuo Wang, Xinyu Zhang, Yanbin Hao, Chengbing Wang, Xiangnan He, MM 2022 (Full, Accept Rate: 27.9%). PDF
[16] Hierarchical Hourglass Convolutional Network for Efficient Video Classification, Yi Tan, Yanbin Hao, Hao Zhang, Shou Wang, Xiangnan He, MM 2022 (Full, Accept Rate: 27.9%). PDF
[17] Parameterization of Cross-Token Relations with Relative Positional Encoding for Vision MLP, Zhicai Wang, Yanbin Hao, Xingyu Gao, Hao Zhang, Shuo Wang, Tingting Mu, Xiangnan He, MM 2022 (Full, Accept Rate: 27.9%). PDF
[18] Unsupervised Video Hashing with Multi-granularity Contextualization and Multi-structure Preservation, Yanbin Hao, Jingru Duan, Hao Zhang, Bin Zhu, Pengyuan Zhou, Xiangnan He, MM 2022 (Full, Accept Rate: 27.9%). PDF
[19] Invariant Representation Learning for Multimedia Recommendation, Xiaoyu Du, Zike Wu, Fuli Feng, Xiangnan He, Jinhui Tang, MM 2022 (Full, Accept Rate: 27.9%). PDF
[20] Reinforced Causal Explainer for Graph Neural Networks, Xiang Wang, Yingxin Wu, An Zhang, Fuli Feng, Xiangnan He, Tat-Seng Chua, TPAMI 2022. PDF
[21] Let Invariant Rationale Discovery Inspire Graph Contrastive Learning, Sihang Li, Xiang Wang, An Zhang, Ying-Xin Wu, Xiangnan He, Tat-Seng Chua, ICML 2022 (Full, Accept Rate: 21.9%). PDF
[22] Addressing Unmeasured Confounder for Recommendation with Sensitivity Analysis, Sihao Ding, Peng Wu, Fuli Feng, Yitong Wang, Xiangnan He, Yong Liao, Yongdong Zhang, KDD 2022 (Full, Accept Rate: 21.9%). PDF
[23] Causal Attention for Interpretable and Generalizable Graph Classification, Yongduo Sui, Xiang Wang, Jiancan Wu, Min Lin, Xiangnan He, Tat-Seng Chua, KDD 2022 (Full, Accept Rate: 21.9%). PDF
In the year of 2021:
[1] Bias and Debias in Recommender System: A Survey and Future Directions, Jiawei Chen, Hande Dong, Xiang Wang, Fuli Feng, Meng Wang, Xiangnan He, arXiv:2010.03240
[2] Denoising Implicit Feedback for Recommendation, Wenjie Wang, Fuli Feng, Xiangnan He, Liqiang Nie, Tat-Seng Chua,In Proceedings of the 14th ACM Web Search and Data Mining, WSDM 2021 (Full, Accept rate: 18.6%). PDF
[3] Seamlessly Unifying Atributes and Items: Conversational Recommendation for Cold-Start Users. Shijun Li, Wenqiang Lei, Qingyun Wu, Xiangnan He, Peng Jiang, Tat-Seng Chua. ACM Transactions on Information Systems (TOIS 2021). PDF
[4] On the Equivalence of Decoupled Graph Convolution Network and Label Propagation, Hande Dong, Jiawei Chen, Fuli Feng, Xiangnan He, Shuxian Bi, Zhaolin Ding & Peng Cui, WWW 2021 (Full, Accept rate: 20.6%). PDF Codes
[5] Disentangling User Interest and Conformity for Recommendation with Causal Embedding, Yu Zheng, Chen Gao, Xiang Li, Xiangnan He, Yong Li & Depeng Jin, WWW 2021 (Full, Accept rate: 20.6%). PDF Codes
[6] Learning Intents behind Interactions with Knowledge Graph for Recommendation,Xiang Wang, Tinglin Huang, Dingxian Wang, Yancheng Yuan, Zhenguang Liu, Xiangnan He & Tat-Seng Chua, WWW 2021 (Full, Accept rate: 20.6%). PDF Codes
[7] Advances and Challenges in Conversational Recommender Systems: A Survey, Chongming Gao, Wenqiang Lei, Xiangnan He, Maarten de Rijke & Tat-Seng Chua, AI Open PDF
[8] Causal Intervention for Leveraging Popularity Bias in Recommendation, Yang Zhang, Fuli Feng, Xiangnan He, Tianxin Wei, Chonggang Song, Guohui Ling & Yongdong Zhang, SIGIR 2021(Full Accept rate: 21%). PDF Best Paper Honorable Mention
[9] AutoDebias: Learning to Debias for Recommendation, Jiawei Chen, Hande Dong, Yang Qiu, Xiangnan He, Xin Xin, Liang Chen, Guli Lin & Keping Yang, SIGIR 2021(Full Accept rate: 21%). PDF
[10] Self-supervised Graph Learning for Recommendation, Jiancan Wu, Xiang Wang, Fuli Feng, Xiangnan He, Liang Chen, Jianxun Lian & Xing Xie, SIGIR 2021(Full Accept rate: 21%). PDF
[11] Clicks can be Cheating: Counterfactual Recommendation for Mitigating Clickbait Issue, Wenjie Wang, Fuli Feng, Xiangnan He, Hanwang Zhang & Tat-Seng Chua, SIGIR 2021(Full Accept rate: 21%). PDF
[12] Should Graph Convolution Trust Neighbors? A Simple Causal Inference Method, Fuli Feng, Weiran Huang, Xin Xin, Xiangnan He, Tat-Seng Chua & Qifan Wang, SIGIR 2021(Full, Accept rate: 21%). PDF
[13] Model-Agnostic Counterfactual Reasoning for Eliminating Popularity Bias in Recommender System, Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu, Jinfeng Yi & Xiangnan He, KDD 2021(Full Accept rate:15.4%). PDF
[14] Deconfounded Recommendation for Alleviating Bias Amplification, Wenjie Wang, Fuli Feng, Xiangnan He, Xiang Wang & Tat-Seng Chua, KDD 2021(Full Accept rate: 15.4%). PDF
[15] Cross-GCN: Enhancing Graph Convolutional Network with k-Order Feature Interactions, Fuli Feng, Xiangnan He*, Hanwang Zhang & Tat-Seng Chua, TKDE 2021. PDF
[16] Adversarial Attack on Large Scale Graph, Jintang Li, Tao Xie, Liang Chen, Fenfang Xie, Xiangnan He & Zibin Zeng, TKDE 2021. PDF
[17] Graph Convolution Machine for Context-aware Recommender System, Jiancan Wu, Xiangnan He*, Xiang Wang, Qifan Wang, Weijian Chen, Jianxun Lian & Xing Xie, Frontiers of Computer Science (FOCS 2021). PDF
[18] On Disambiguating Authors: Collaboration Network Reconstruction in a Bottom-up Manner, Na Li, Renyu Zhu, Xiaoxu Zhou, Xiangnan He, Wenyuan Cai, Ming Gao, Aoying Zhou, ICDE 2021. PDF
[19] Selective Dependency Aggregation for Action Classification, Yi Tan, Yanbin Hao, Xiangnan He, Yinwei Wei, Xun Yang, MM 2021(Full Accept rate: 28%). PDF
[20] A Survey on Neural Recommendation: From Collaborative Filtering to Content and Context Enriched Recommendation, Le Wu, Xiangnan He, Xiang Wang, Kun Zhang, Meng Wang, PDF
[21] Structure-Enhanced Meta-Learning For Few-Shot Graph Classification, Shunyu Jiang, Fuli Feng, Weijian Chen, Xiang Li, Xiangnan He, AI Open. PDF
[22] DisenKGAT: Knowledge Graph Embedding with Disentangled Graph Attention Network, Junkang Wu, Wentao Shi, Xuezhi Cao, Jiawei Chen, Wenqiang Lei, Fuzheng Zhang, Wei Wu, Xiangnan He, CIKM 2021 (Full, Accept rate: 21.3%). PDF
[23] A Deep Learning Framework for Self-evolving Hierarchical Community Detection, Daizong Ding, Mi Zhang, Hanrui Wang, Xudong Pan, Min Yang, Xiangnan He, CIKM 2021 (Full, Accept rate: 21.3%). PDF
[24] Towards Multi-Grained Explainability for Graph Neural Networks, Xiang Wang, Yingxin Wu, An Zhang, Xiangnan He & Tat-Seng Chua, NeuIPS 2021 (Full, Accept rate: 26%). PDF
In the year of 2020:
[1] LightGCN: Simplifying and Powering Graph Convolution Network for Recommendation, Xiangnan He, Kuan Deng, Xiang Wang, Yan Li, Yongdong Zhang and Meng Wang, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF Codes
[2] How to Retrain a Recommender System? A Sequential Meta-Learning Approach, Yang Zhang, Fuli Feng, Xiangnan He, Chenxu Wang, Meng Wang, Yan Li and Yongdong Zhang, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF Codes
[3] Parameter-Efficient Transfer from Sequential Behaviors for User Modeling and Recommendation, Fajie Yuan, Xiangnan He, Alexandros Karatzoglou and Liguang Zhang, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF Codes
[4] Modeling Personalized Item Frequency Information for Next-basket Recommendation, Haoji Hu, Xiangnan He*, Jinyang Gao and Zhi-Li Zhang, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF Codes *Corresponding author
[5] Disentangled Representations for Graph-based Collaborative Filtering, Xiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu and Tat-Seng Chua, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF Codes
[6] Hierarchical Fashion Graph Network for Personalised Outfit Recommendation, Xingchen Li, Xiang Wang, Xiangnan He, Long Chen, Jun Xiao and Tat-Seng Chua, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF Codes
[7] Certifiable Robustness to Discrete Adversarial Perturbations for Factorization Machines, Yang Liu, Xianzhuo Xia, Liang Chen, Xiangnan He, Carl Yang and Zibin Zheng, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF
[8] Multi-behavior Recommendation with Graph Convolution Networks, Bowen Jin, Chen Gao, Xiangnan He, Yong Li and Depeng Jin, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (Full, Accept rate: 26%). PDF
[9] Bundle Recommendation with Graph Convolutional Networks, Jianxin Chang, Chen Gao, Xiangnan He, Yong Li and Depeng Jin, In Proceedings of the 43nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2020 (short). PDF Codes Best Short Paper Honorable Mention
[10] Bilinear Graph Neural Network with Neighbor Interactions, Hongmin Zhu, Fuli Feng, Xiangnan He, Xiang Wang, Yan Li, Kai Zheng & Yongdong Zhang, In Proceedings of the 29th International Joint Conference on Artificial Intelligence, IJCAI 2020 (Full, Accept rate: 12.6%). PDF Codes
[11] Reinforced Negative Sampling over Knowledge Graph for Recommendation, Xiang Wang, Yaokun Xu, Xiangnan He, Yixin Cao, Weng Wang & Tat-Seng Chua, In Proceedings of the 29th International Conference on World Wide Web, WWW 2020 (Full, Accept rate: 19%). PDF Codes
[12] Future Data Helps Training: Modelling Future Contexts for Session-based Recommendation, Fajie Yuan, Xiangnan He, Haochuan Jiang, Guibing Guo, Jian Xiong, Zhezhao Xu & Xiong Yilin, In Proceedings of the 29th International Conference on World Wide Web, WWW 2020 (Full, Accept rate:19%). PDF Codes Slides
[13] Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems, Wenqiang Lei, Xiangnan He*, Yisong Miao, Qingyun Wu, Richang Hong, Min-Yen Kan & Tat-Seng Chua, In Proceedings of the 13th ACM International Conference on Web Search and Data Mining, WSDM 2020 (Full, Accept rate:15%). PDF Codes Slides *Corresponding author
[14] Price-aware Recommendation with Graph Convolutional Networks, Yu Zheng, Chen Gao, Xiangnan He, Yong Li & Depeng Jin, In Proceedings of the 36th IEEE International Conference on Data Engineering, ICDE 2020 (Full). PDF
[15] Improving Neural Relation Extraction with Implicit Mutual Relations, Jun Kuang, Yixin Cao, Jianbing Zheng, Xiangnan He, Ming Gao & Aoying Zhou, In Proceedings of the 36th IEEE International Conference on Data Engineering, ICDE 2020 (Full). PDF
[16] Syndrome-aware Herb Recommendation with Multi-Graph Convolution Network, Yuanyuan Jin, Wei Zhang, Xiangnan He, Xinyu Wang & Xiaoling Wang, In Proceedings of the 36th IEEE International Conference on Data Engineering, ICDE 2020 (Full). PDF
[17] Improving the Robustness of Wasserstein Embedding by Adversarial PAC-Bayesian Learning, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang & Xiangnan He, In Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2020 (Full, Accept rate:20.6%). PDF
[18] Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction, Haozhe Wu, Zhiyuan Hu, Jia Jia, Yaohua Bu, Xiangnan He & Tat-Seng Chua, In Proceedings of the 24th AAAI Conference on Artificial Intelligence, AAAI 2020 (Full, Accept rate:20.6%). PDF
[19] Interactive Path Reasoning on Graph for Conversational Recommendation, Wenqiang Lei, Gangyi Zhang, Xiangnan He*, Yisong Miao, Xiang Wang, Liang Chen and Tat-Seng Chua, In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2020 (Full, Accept rate: 16.9%). PDF *Corresponding author
[20] Enterprise Cooperation and Competition Analysis with Sign-Oriented Preference Network, Le Dai, Yu Yin, Chuan Qin, Tong Xu, Xiangnan He, Enhong Chen and Hui Xiong, In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2020 (Full, Accept rate: 16.9%). PDF
[21] Graph-Refined Convolutional Network for Multimedia Recommendation with Implicit Feedback, Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Tat-Seng Chua, In Proceedings of the 28th ACM International Conference on Multimedia, MM 2020 (Full, Accept rate: 27.8%). PDF
[22] How to Learn Item Representation for Cold-Start Multimedia Recommendation?, Xiaoyu Du, Xiang Wang, Xiangnan He, Zechao Li, Jinhui Tang, Tat-Seng Chua, In Proceedings of the 28th ACM International Conference on Multimedia, MM 2020 (Full, Accept rate: 27.8%). PDF
[23] Heterogeneous Fusion of Semantic and Collaborative Information for Visually-Aware Food Recommendation, Lei Meng, Fuli Feng, Xiangnan He, Xiaoyan Gao, Tat-Seng Chua, In Proceedings of the 28th ACM International Conference on Multimedia, MM 2020 (Full, Accept rate: 27.8%). PDF
[24] STRONG: Spatio-Temporal Reinforcement Learning for Cross-Modal Video Moment Localization, Da Cao, Yawen Zeng, Meng Liu, Xiangnan He, Meng Wang, Zheng Qin, In Proceedings of the 28th ACM International Conference on Multimedia, MM 2020 (Full, Accept rate: 27.8%). PDF
[25] Fast Adaptation for Cold-start Collaborative Filtering with Meta-learning. Tianxin Wei, Ziwei Wu, Ruirui Li, Ziniu Hu, Fuli Feng, Xiangnan He, Yizhou Sun, and Wei Wang. In Proceedings of the 20th IEEE International Conference on Data Mining, ICDM 2020 (full, accept rate: 9.8%). PDF
[26] Modeling Personalized Out-of-Town Distances in Location Recommendation. Daizong Ding, Mi Zhang, Xudong Pan, Min Yang, and Xiangnan He. In Proceedings of the 20th IEEE International Conference on Data Mining, ICDM 2020 (full, accept rate: 9.8%). PDF
In the year of 2019:
[1] Neural Graph Collaborative Filtering, Xiang Wang, Xiangnan He*, Meng Wang, Fuli Feng & Tat-Seng Chua, In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, pp. 165-174. PDF Codes Slides *Corresponding author
[2] Relational Collaborative Filtering: Modeling Multiple Item Relations for Recommendaton, Xin Xin, Xiangnan He*, Yongfeng Zhang, Yongdong Zhang & Joemon Jose, In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, pp. 125-134. PDF Codes Slides *Corresponding author
[3] Interpretable Fashion Matching with Rich Attributes, Xun Yang, Xiangnan He, Xiang Wang, Yunshan Ma, Fuli Feng, Meng Wang & Tat-Seng Chua, In Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2019, pp. 775-784. PDF Slides
[4] KGAT: Knowledge Graph Attention Network for Recommendation, Xiang Wang, Xiangnan He*, Yixin Cao, Meng Liu & Tat-Seng Chua, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019 (Full, Accept rate: 14.2%), pp. 950-958. PDF Codes Poster *Corresponding author
[5] Sets2Sets: Learning from Sequential Sets with Neural Networks, Haoji Hu, Xiangnan He*, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019 (Full, Accept rate: 14.2%), pp. 1491-1499. PDF Codes *Corresponding author
[6] λOpt: Learn to Regularize Recommender Models in Finer Levels, Yihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou & Yue Wang, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019 (Full Oral, Accept rate: 9.2%), pp. 978-986. PDF Codes Slides Poster
[7] Modeling Extreme Events in Time Series Prediction, Daizong Ding, Mi Zhang, Xudong Pan, Min Yang & Xiangnan He, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2019 (Full Oral, Accept rate: 9.2%), pp. 1114-1122. PDF Slides Poster
[8] Counterfactual Critic Multi-Agent Training for Scene Graph Generation, Long Cheng, Hanwang Zhang, Jun Xiao, Xiangnan He, Shiliang Pu & Shih-Fu Chang, ICCV 2019 (Oral, Accept rate: 4.3%). PDF
[9] MMGCN: Multimodal Graph Convolution Network for Personalized Recommendation of Micro-video, Yinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Richang Hong & Tat-Seng Chua, In Proceedings of the 27th ACM International Conference on Multimedia, MM 2019 (Full, Accept rate: 26.5%), pp. 1437-1445. PDF Codes
[10] Mixed-dish Recognition with Contextual Relation Network, Lixi Deng, Jingjing Chen, Qianru Sun, Xiangnan He, Sheng Tang, Zhaoyan Ming, Yongdong Zhang & Tat-Seng Chua, In Proceedings of the 27th ACM International Conference on Multimedia, MM 2019 (Full, Accept rate: 26.5%), pp. 112-120. PDF
[11] Learning Subjective Attributes of Images from Auxiliary Sources, Francesco Gelli, Tiberio Uricchio, Xiangnan He, Alberto Del Bimbo & Tat-Seng Chua, In Proceedings of the 27th ACM International Conference on Multimedia, MM 2019 (Full, Accept rate: 26.5%), pp. 2263-2271. PDF Codes
[12] Reinforced Negative Sampling for Recommendation with Exposure Data, Jingtao Ding, Yuhan Quan, Xiangnan He, Yong Li & Depeng Jin, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 (Full, Accept rate: 17.9%), pp. 2230-2236. PDF Codes Slides
[13] CFM: Convolutional Factorization Machines for Context-Aware Recommendation, Xin Xin, Bo Chen, Xiangnan He, Dong Wang, Yue Ding & Joemon Jose, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 (Full, Accept rate: 17.9%), pp. 3926-3932. PDF Codes Slides
[14] Matching User with Item Set: Collaborative Bundle Recommendation with Attention Network, Liang Chen, Yang Liu, Xiangnan He, Lianli Gao & Zibin Zheng, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 (Full, Accept rate: 17.9%), pp. 2095-2101. PDF Slides
[15] Enhancing Stock Movement Prediction with Adversarial Training, Fuli Feng, Huimin Chen, Xiangnan He*, Maosong Sun, Tat-Seng Chua & Ji Ding, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 (Full, Accept rate: 17.9%), pp. 5843-5849. PDF Codes Slides *Corresponding author
[16] Semi-supervised User Profiling with Heterogeneous Graph Attention Networks, Weijian Chen, Yulong Gu, Zhaochun Ren*, Xiangnan He*, Hongtao Xie, Tong Guo, Dawei Yin & Yongdong Zhang, In Proceedings of the 28th International Joint Conference on Artificial Intelligence, IJCAI 2019 (Full, Accept rate: 17.9%), pp. 2116-2122. PDF Codes Slides *Corresponding author
[17] Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preference, Yixin Cao, Xiang Wang, Xiangnan He*, Zikun Hu & Tat-Seng Chua, In Proceedings of the 28th International Conference on World Wide Web, WWW 2019 (Full, Accept rate: 18%), pp. 151-161. PDF Codes *Corresponding author
[18] Cross-domain Recommendation Without Sharing User-relevant Data, Chen Gao, Xiangning Chen, Fuli Feng, Kai Zhao, Xiangnan He, Yong Li & Depeng Jin, In Proceedings of the 28th International Conference on World Wide Web, WWW 2019 (Full, Accept rate: 18%), pp. 491-502. PDF Codes Slides
[19] Explainable Reasoning over Knowledge Graph Paths for Recommendation, Xiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao & Tat-Seng Chua, In Proceedings of the 23th AAAI Conference on Artificial Intelligence, AAAI 2019 (Full, Accept rate: 16.2%), pp. 5329-5336. PDF Codes Slides
[20] Beyond RNNs: Positional Self-Attention with Co-Attention for Video Question Answering, Xiangpeng Li, Jingkuan Song, Lianli Gao, Xianglong Liu, Wenbing Huang, Chuang Gan & Xiangnan He, In Proceedings of the 23th AAAI Conference on Artificial Intelligence, AAAI 2019 (Full, Accept rate: 16.2%), pp. 8658-8665. PDF
[21] A Simple Convolutional Generative Network for Next-item Recommendation, Fajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose & Xiangnan He, Proceedings of the 12th ACM International Conference on Web Search and Data Mining, WSDM 2019 (Full, Accept rate: 16.4%), pp. 582-590. PDF Codes
[22] Neural Multi-Task Recommendation from Multi-Behavior Data, Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua & Depeng Jin, In Proceedings of the 35th IEEE International Conference on Data Engineering, ICDE 2019 (Short), pp. 1554-1557. PDF
In the year of 2018:
[1] Adversarial Personalized Ranking for Recommendation. Xiangnan He, Zhankui He, Xiaoyu Du, and Tat-Seng Chua. In Proceedings of the 41th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2018, Full, Accept rate: 21%), pp. 355-364. PDF Codes Slides
[2] Attentive Group Recommendation. Da Cao, Xiangnan He, Lianhai Miao, Yahui An, Chao Yang, and Richang Hong. In Proceedings of the 41th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2018, Full, Accept rate: 21%), pp. 645-654. PDF Codes Slides
[3] BiNE: Bipartite Network Embedding. Ming Gao, Leihui Chen, Xiangnan He*, and Aoying Zhou. In Proceedings of the 41th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2018, Full, Accept rate: 21%), pp. 715-724. PDF Codes Slides *Corresponding author
[4] Fast Scalable Supervised Hashing. Xin Luo, Liqiang Nie, Xiangnan He, Ye Wu, Zhen-Duo Chen, and Xin-Shun Xu. In Proceedings of the 41th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2018, Full, Accept rate: 21%), pp. 735-744. PDF Codes Slides
[5] Attentive Moment Retrieval in Videos. Meng Liu, Xiang Wang, Liqiang Nie, Xiangnan He, Baoquan Chen and Tat-Seng Chua. In Proceedings of the 41th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2018, Full, Accept rate: 21%), pp. 15-24. PDF Codes Slides
[6] A Personal Privacy Preserving Framework: I Let You Know Who Can See What. Xuemeng Song, Xiang Wang, Liqiang Nie, Xiangnan He, Zhumin Chen, and Wei Liu. In Proceedings of the 41th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2018, Full, Accept rate: 21%), pp. 295-304. PDF Codes Slides
[7] Outer Product-based Neural Collaborative Filtering. Xiangnan He, Xiaoyu Du, Xiang Wang, Feng Tian, Jinhui Tang, and Tat-Seng Chua. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018, Full, Accept rate: 20.5%), pp. 2227-2233. PDF Codes Slides
[8] Improving Implicit Recommender Systems with View Data. Jingtao Ding, Guanghui Yu, Xiangnan He*, Yuhan Quan, Yong Li, Tat-Seng Chua, Depeng Jin, and Jiajie Yu. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018, Full, Accept rate: 20.5%), pp. 3343-3349. PDF Codes Slides *Corresponding author
[9] Discrete Factorization Machines for Fast Feature-based Recommendation. Han Liu, Xiangnan He, Fuli Feng, Liqiang Nie, Rui Liu, and Hanwang Zhang. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018, Full, Accept rate: 20.5%), pp. 3449-3455. PDF Codes Slides
[10] A3ˆNCF: An Adaptive Aspect Attention Model for Rating Prediction. Zhiyong Cheng, Ying Ding, Xiangnan He, Lei Zhu, Xuemeng Song, and Mohan Kankanhalli. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018, Full, Accept rate: 20.5%), pp. 3748-3754. PDF Codes Slides
[11] Cross-Domain Depression Detection via Harvesting Social Media. Tiancheng Shen , Jia Jia , Guangyao Shen, Fuli Feng, Xiangnan He, Huanbo Luan, Jie Tang, Tiropanis Thanassis, Tat-Seng Chua, and Wendy Hall. In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI 2018, Full, Accept rate: 20.5%), pp. 1611-1617. PDF Slides
[12] fBGD: Learning Embeddings From Positive-Only Data with BGD. Fajie Yuan, Xin Xin, Xiangnan He, Guibing Guo, Weinan Zhang, Tat-Seng Chua, and Joemon Jose. In Proceedings of the Thirty-Fourth Conference on Uncertainty in Artificial Intelligence (UAI 2018, Full). PDF Codes
[13] TEM: Tree-enhanced Embedding Model for Explainable Recommendation. Xiang Wang, Xiangnan He*, Fuli Feng, Liqiang Nie, and Tat-Seng Chua. In Proceedings of the 27th International Conference on World Wide Web (WWW 2018, Accept rate: 14.8%), pp. 1543-1552. PDF Slides *Corresponding author
[14] Learning on Partial-Order Hypergraphs. Fuli Feng, Xiangnan He, Yiqun Liu, Liqiang Nie, and Tat-Seng Chua. In Proceedings of the 27th International Conference on World Wide Web (WWW 2018, Accept rate: 14.8%), pp. 1523-1532. PDF Codes Slides
[15] Aesthetic-based Clothing Recommendation. Wenhui Yu, Huidi Zhang, Xiangnan He, Xu Chen, Li Xiong, and Zheng Qin. In Proceedings of the 27th International Conference on World Wide Web (WWW 2018), pp. 649-658. PDF Codes Slides Best Paper Award Honorable Mention
[16] An Improved Sampler for Bayesian Personalized Ranking by Leveraging View Data. Jingtao Ding, Fuli Feng, Xiangnan He, Guanghui Yu, Yong Li, and Depeng Jin. In Proceedings of the 27th International Conference on World Wide Web (WWW 2018, Poster), pp. 13-14. PDF Codes Best Poster Award
[17] Batch IS NOT Heavy: Learning Word Embeddings From All Samples. Xin Xin, Fajie Yuan, Xiangnan He*, and Joemon Jose. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2018, Full), pp. 1853-1862. PDF Codes Slides *Corresponding author
[18] Sequicity: Simplifying Task-oriented Dialogue Systems with Single Sequence-to-Sequence Architectures. Wenqiang Lei, Xisen Jin, Min-Yen Kan, Zhaochun Ren, Xiangnan He, and Dawei Yin. In Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2018, Full), pp. 1437-1447. PDF Codes Slides
[19] Venue Prediction for Social Images by Exploiting Rich Temporal Patterns in LBSNs. Jingyuan Chen, Xiangnan He, Xuemeng Song, Hanwang Zhang, Liqiang Nie, and Tat-Seng Chua. In Proceedings of the 24th International Conference on Multimedia Modeling (MMM 2018), pp. 327-339. PDF Poster
[20] A Graph-Theoretic Fusion Framework for Unsupervised Entity Resolution. Dongxiang Zhang, Long Guo, Xiangnan He, Jie Shao, Sai Wu, and Heng Tao Shen. In Proceedings of the 34th IEEE International Conference on Data Engineering (ICDE 2018), pp. 713-724. PDF Slides
[21] Group-pair Convolutional Neural Networks for Multi-view based 3D Object Retrieval. Zan Gao, Yu Wang, Xiangnan He, and Hua Huang. In Proceedings of the 22th AAAI Conference on Artificial Intelligence (AAAI 2018, Accept rate: 24.6%), pp. 2223-2231. PDF Slides
In the year of 2017:
[1] Neural Factorization Machines for Sparse Predictive Analytics. Xiangnan He and Tat-Seng Chua. In Proceedings of the 40th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2017, Accept rate: 22%), pp. 355-364. PDF Codes Slides
[2] Item Silk Road: Recommending Items from Information Domains to Social Users. Xiang Wang, Xiangnan He*, Liqiang Nie, and Tat-Seng Chua. In Proceedings of the 40th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2017, Accept rate: 22%), pp. 185-194. PDF Codes Slides *Corresponding author
[3] Embedding Factorization Models for Jointly Recommending User Generated Lists and Their Contained Items. Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Shuizhi Zhu, Shunxiang Wu, Tat-Seng Chua. In Proceedings of the 40th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2017, Accept rate: 22%), pp. 585-594. PDF Codes Slides
[4] Attentive Collaborative Filtering: Multimedia Recommendation with Component- and Item-Level Attention. Jingyuan Chen, Hanwang Zhang, Xiangnan He*, Liqiang Nie, Wei Liu, and Tat-Seng Chua. In Proceedings of the 40th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2017, Accept rate: 22%), pp. 335-344. PDF Codes Slides *Corresponding author
[5] Neural Collaborative Filtering. Xiangnan He, Lizi Liao, Hanwang Zhang, Liqiang Nie, Xia Hu, and Tat-Seng Chua. In Proceedings of the 26th International Conference on World Wide Web (WWW 2017, Accept rate: 17%), pp. 173-182. PDF Codes Slides
[6] A Generic Coordinate Descent Framework for Learning from Implicit Feedback. Immanuel Bayer*, Xiangnan He*, Bhargav Kanagal, and Steffen Rendle. In Proceedings of the 26th International Conference on World Wide Web (WWW 2017, Accept rate: 17%), pp. 1341-1350. PDF *Joint work at Google
[7] How Personality Affects our Likes: Towards a Better Understanding of Actionable Images. Francesco Gelli, Xiangnan He*, Tao Chen, and Tat-Seng Chua. In Proceedings of the 2017 ACM on Multimedia Conference (MM 2017, Full oral), pp. 1828-1837. PDF Codes Slides *Corresponding author
[8] Enhancing Micro-video Understanding by Harnessing External Sounds. Liqiang Nie, Xiang Wang, Jianglong Zhang, Xiangnan He, Hanwang Zhang, Richang Hong, and Qi Tian. In Proceedings of the 2017 ACM on Multimedia Conference (MM 2017, Full oral), pp. 1192-1200. PDF
[9] Multiview and Multimodal Pervasive Indoor Localization. Zhenguang Liu, Li Cheng, Anan Liu, Luming Zhang, Xiangnan He, and Roger Zimmermann. In Proceedings of the 2017 ACM on Multimedia Conference (MM 2017, Full poster), pp. 109-117. PDF
[10] Video Question Answering via Gradually Refined Attention over Appearance and Motion. Dejing Xu, Zhou Zhao, Jun Xiao, Fei Wu, Hanwang Zhang, Xiangnan He, and Yueting Zhuang. In Proceedings of the 2017 ACM on Multimedia Conference (MM 2017, Full poster), pp. 1645-1653. PDF
[11] Representativeness-aware Aspect Analysis for Brand Monitoring in Social Media. Lizi Liao, Xiangnan He, Zhaochun Ren, Liqiang Nie, Huan Xu, and Tat-Seng Chua. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017, Accept rate: 26%), pp. 310-316. PDF Slides *Corresponding author
[12] Attentional Factorization Machines: Learning the Weight of Feature Interactions via Attention Networks. Jun Xiao, Hao Ye, Xiangnan He*, Hanwang Zhang, Fei Wu, and Tat-Seng Chua. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017, Accept rate: 26%), pp. 3119-3125. PDF Codes Slides *Corresponding author
[13] SWIM: A Simple Word Interaction Model for Implicit Discourse Relation Recognition. Wenqiang Lei, Xuancong Wang, Meichun Liu, Ilija Ilievski, Xiangnan He, and Min-Yen Kan. In Proceedings of the 26th International Joint Conference on Artificial Intelligence (IJCAI 2017, Accept rate: 26%), pp. 4026-4032. PDF Slides
Before 2017:
[1] Fast Matrix Factorization for Online Recommendation with Implicit Feedback. Xiangnan He, Hanwang Zhang, Min-Yen Kan, and Tat-Seng Chua. In Proceedings of the 39th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2016, Accept rate: 18%), pp. 549-558. PDF Codes Slides
[2] Discrete Collaborative Filtering. Hanwang Zhang, Fumin Shen, Wei Liu, Xiangnan He, Huanbo Luan, and Tat-Seng Chua. In Proceedings of the 39th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2016, Accept rate: 18%), pp. 325-334. PDF Codes Slides Best Paper Award Honorable Mention
[3] Context-aware Image Tweets Modelling and Recommendation. Tao Chen, Xiangnan He, and Min-Yen Kan. In Proceedings of the 2016 ACM on Multimedia Conference (MM 2016, Accept rate: 20%), pp. 1018-1027. PDF Codes
[4] Shorter-is-Better: Venue Category Estimation from Micro-Video. Jianglong Zhang, Liqiang Nie, Xiang Wang, Xiangnan He, Xianglin Huang, and Tat-Seng Chua. In Proceedings of the 2016 ACM Conference on Multimedia Conference (MM 2016, Accept rate: 20%), pp. 1415-1424. PDF Codes
[5] TriRank: Review-aware Explainable Recommendation by Modeling Aspects. Xiangnan He, Tao Chen, Min-Yen Kan, and Xiao Chen. In Proceedings of the 24th ACM International on Conference on Information and Knowledge Management (CIKM 2015, Accept rate: 18%), pp. 1661-1670. PDF Slides
[6] VELDA: Relating an Image Tweets Text and Images. Tao Chen, Hany Salaheldeen, Xiangnan He, Min-Yen Kan, and Dongyuan Lu. In Proceedings of the 27th AAAI Conference on Artificial Intelligence (AAAI 2015, Accept rate: 26.7%), pp. 30-37. PDF Codes
[7] Differential Spread Strategy: an Incentive for Advertisement Dissemination. Xiao Chen, Min Liu, Yaqin Zhou, Shuang Chen, and Xiangnan He. In IEEE Symposium on Computers and Communication (ISCC 2015), pp. 595–601. PDF
[8] Predicting the Popularity of Web 2.0 Items Based on User Comments. Xiangnan He, Ming Gao, Min-Yen Kan, Yiqun Liu, and Kazunari Sugiyama. In Proceedings of the 37th International ACM SIGIR Conference on Research & Development in Information Retrieval (SIGIR 2014, Accept rate: 21%), pp. 233-243. PDF Slides
[9] Comment-based Multi-View Clustering of Web 2.0 Items. Xiangnan He, Min-Yen Kan, Peichu Xie, and Xiao Chen. In Proceedings of the 23rd International Conference on World Wide Web (WWW 2014), pp. 771-782. PDF Supplement Slides Codes
[10] Mining Scientific Terms and their Definitions: A Study of the ACL Anthology. Yiping Jin, Min-Yen Kan, Jun-Ping Ng, and Xiangnan He. In Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing (EMNLP 2013), pp. 780-790. PDF
Journal papers：
From year 2017 to now
[1] Modelling High-Order Social Relations for Item Recommendation, Yang Liu, Liang Chen, Xiangnan He, Jiaying Peng, Zibin Zheng, Jie Tang, IEEE Transactions on Knowledge and Data Engineering (TKDE 2021). PDF
[2] Learning Vertex Representations for Bipartite Networks. Ming Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang Aoying Zhou, IEEE Transactions on Knowledge and Data Engineering (TKDE 2020). PDF Codes
[3] Learning Visual Elements of Images for Discovery of Brand Posts. Francesco Gelli, Tiberio Uricchio*, Xiangnan He*, Alberto Del Bimbo & Tat-Seng Chua, IEEE Transactions on Multimedia Computing Communications and Applications (TOMM 2020). PDF *Corresponding author
[4] Graph Adversarial Training: Dynamically Regularizing Based on Graph Structure. Fuli Feng, Xiangnan He*, Jie Tang & Tat-Seng Chua, IEEE Transactions on Knowledge and Data Engineering (TKDE 2020). PDF Codes *Corresponding author
[5] Learning to Recommend with Multiple Cascading Behaviors. Chen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li & Tat-Seng Chua, IEEE Transactions on Knowledge and Data Engineering (TKDE 2020). PDF
[6] Modeling Product's Visual and Functional Characteristics for Recommender Systems. Bin Wu, Xiangnan He, Yun Chen, Liqiang Nie, Kai Zheng, Yangdong Ye. IEEE Transactions on Knowledge and Data Engineering (TKDE 2020). PDF
[7] Improving Implicit Recommender Systems with Auxiliary Data. Jingtao Ding, Guanghui Yu, Yong Li, Xiangnan He, & Depeng Jin, ACM Transactions on Information Systems (TOIS 2020). PDF
[8] ATM: An Attentive Translation Model for Next-Item Recommendation. Bin Wu, Xiangnan He, Zhongchuan Sun, Liang Chen & Yangdong Ye, IEEE Transactions on Industrial Informatics (TII 2020). PDF
[9] Generating Face Images with Attributes for Free. Yaoyao Liu, Qianru Sun, Xiangnan He, An-An Liu, Yuting Su, and Tat-Seng Chua, IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2020). PDF
[10] Fast Matrix Factorization with Non-Uniform Weights on Missing Data, Xiangnan He, Jinhui Tang, Xiaoyu Du, Richang Hong, Tongwei Ren & Tat-Seng Chua, IEEE Transactions on Neural Networks and Learning Systems (TNNLS 2020). PDF Codes
[11] A Survey on Large-scale Machine Learning, Meng Wang, Weijie Fu, Xiangnan He, Shijie Hao, Xindong Wu,IEEE Transactions on Knowledge and Data Engineering (TKDE 2020). PDF
[12] Socializing the Videos: A Multimodal Approach for Social Relation Recognition, Tong Xu, Peilun Zhou, Linkang Hu, Xiangnan He, Yao Hu, Enhong Chen, ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM2020). PDF
[13] Social-enhanced Attentive Group Recommendation, Da Cao, Xiangnan He, Lianhai Miao, Guangyi Xiao, Hao Chen & Richang Hong, IEEE Transactions on Knowledge and Data Engineering (TKDE 2019). PDF
[14] Knowledge Embedding Based Topic Model for Multi-modal Social Event Analysis, Feng Xue, Richang Hong, Xiangnan He, Jianwei Wang, Shengsheng Qian, Tianzhu Zhang & Changsheng Xu, IEEE Transactions on Multimedia (TMM 2019). PDF
[15] Hierarchical Attention Network for Visually-aware Food Recommendation, Xiaoyan Gao, Fuli Feng, Xiangnan He, Heyan Huang, Xinyu Guan, Chong Feng, Zhaoyan Ming, Tat-Seng Chua, IEEE Transactions on Multimedia (TMM 2019). PDF
[16] Learning to Compose and Reason with Language Tree Structures for Visual Grounding, Richang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He & Hanwang Zhang, IEEE Transactions on Pattern Recognition and Machine Intelligence (TPAMI 2019). PDF
[17] Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative Filtering, Xiaoyu Du, Xiangnan He*, Fajie Yuan, Jinhui Tang, Zhiguang Qin & Tat-Seng Chua, ACM Transactions on Information Systems (TOIS 2019). PDF Codes *Corresponding author
[18] Temporal Relational Ranking for Stock Prediction, Fuli Feng, Xiangnan He*, Xiang Wang, Cheng Luo, Yiqun Liu & Tat-Seng Chua, ACM Transactions on Information Systems (TOIS 2019). PDF Codes *Corresponding author
[19] Attentive Aspect Modeling for Review-aware Recommendation, Xinyu Guan, Zhiyong Cheng, Xiangnan He, Yongfeng Zhang, Zhibo Zhu, Qinke Peng & Tat-Seng Chua, ACM Transactions on Information Systems (TOIS 2019). PDF Codes
[20] Adversarial Training Towards Robust Multimedia Recommender System, Jinhui Tang, Xiaoyu Du, Xiangnan He*, Fajie Yuan, Qi Tian & Tat-Seng Chua, IEEE Transactions on Knowledge and Data Engineering (TKDE 2019). PDF Codes *Corresponding author
[21] Sampler Design for Bayesian Personalized Ranking by Leveraging View Data, Jingtao Ding, Guanghui Yu, Xiangnan He, Fuli Feng, Yong Li & Depeng Jin, IEEE Transactions on Knowledge and Data Engineering (TKDE 2019). PDF
[22] Generative Adversarial Active Learning for Unsupervised Outlier Detection, Yezheng Liu, Zhe Li, Chong Zhou, Yuanchun Jiang, Jianshan Sun, Meng Wang & Xiangnan He*, IEEE Transactions on Knowledge and Data Engineering (TKDE 2019). PDF Codes *Corresponding author
[23] Deep Item-based Collaborative Filtering for Top-N Recommendation, Feng Xue, Xiangnan He*, Xiang Wang, Jiandong Xu, Kai Liu & Richang Hong, ACM Transactions on Information Systems (TOIS 2019). PDF Codes *Corresponding author
[24] HoAFM: A High-order Attentive Factorization Machine for CTR Prediction, Zhulin Tao, Xiang Wang, Xiangnan He, Xianglin Huang & Tat-Seng Chua, Information Processing & Management (IPM 2019). PDF
[25] Attributed Social Network Embedding. Lizi Liao, Xiangnan He*, Hanwang Zhang, and Tat-Seng Chua (2018). IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol 30:12, pp. 2257-2270. PDF Codes *Corresponding author
[26] NAIS: Neural Attentive Item Similarity Model for Recommendation. Xiangnan He, Zhankui He, Jingkuan Song, Zhenguang Liu, Yu-Gang Jiang, and Tat-Seng Chua (2018). IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol 30:12, pp. 2354-2366. PDF Codes
[27] BiRank: Towards Ranking on Bipartite Graphs. Xiangnan He, Ming Gao, Min-Yen Kan, and Dingxian Wang (2017). IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol 29:1, pp. 57–71. PDF
[28] Cross-Platform App Recommendation by Jointly Modeling Ratings and Texts. Da Cao, Xiangnan He, Liqiang Nie, Xiaochi Wei, Xia Hu, Shunxiang Wu, and Tat-Seng Chua (2017). ACM Transactions on Information Systems (TOIS), Vol 35:4, pp. 1–27. PDF Codes Slides
[29] Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark Search. Lei Zhu, Zi Huang, Xiaobai Liu, Xiangnan He, Jingkuan Song, and Xiaofang Zhou (2017). IEEE Transactions on Multimedia (TMM), Vol 19:9, pp. 2066-2079. PDF
[30] Version-sensitive mobile App recommendation. Da Cao, Liqiang Nie, Xiangnan He, Xiaochi Wei, Jialie Shen, Shunxiang Wu, and Tat-Seng Chua (2017). Information Sciences, Vol 381:C, pp. 161-175. PDF Codes
[31] A Truthful Incentive Mechanism for Online Recruitment in Mobile Crowd Sensing System. Xiao Chen, Min Liu, Yaqin Zhou, Zhongcheng Li, Shuang Chen, Xiangnan He (2017). Sensors, 17(1):79. PDF
