PUBLICATIONS

Conference papers

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 ApproachYang 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 RecommendationFajie 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 RecommendationHaoji Hu, Xiangnan He*, Jinyang Gao and Zhi-Li ZhangIn 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 FilteringXiang Wang, Hongye Jin, An Zhang, Xiangnan He, Tong Xu and Tat-Seng ChuaIn 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 RecommendationXingchen 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 MachinesYang 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 NetworksBowen 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 NetworksJianxin 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    

[10] Bilinear Graph Neural Network with Neighbor InteractionsHongmin 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 RecommendationXiang 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 RecommendationFajie 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 SystemsWenqiang 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 NetworksYu 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 RelationsJun 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 NetworkYuanyuan 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 LearningDaizong 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 InteractionHaozhe 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   

In the year of 2019:

[1] Neural Graph Collaborative FilteringXiang Wang, Xiangnan He*, Meng Wang, Fuli Feng & Tat-Seng ChuaIn 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 RecommendatonXin Xin, Xiangnan He*, Yongfeng Zhang, Yongdong Zhang & Joemon JoseIn 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 ChuaIn 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 RecommendationXiang Wang, Xiangnan He*, Yixin Cao, Meng Liu & Tat-Seng ChuaIn 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 NetworksHaoji 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 LevelsYihong Chen, Bei Chen, Xiangnan He, Chen Gao, Yong Li, Jian-Guang Lou & Yue WangIn 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 PredictionDaizong Ding, Mi Zhang, Xudong Pan, Min Yang & Xiangnan HeIn 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 GenerationLong Cheng, Hanwang Zhang, Jun Xiao, Xiangnan He, Shiliang Pu & Shih-Fu ChangICCV 2019 (Oral, Accept rate: 4.3%).   PDF 

[9] MMGCN: Multimodal Graph Convolution Network for Personalized Recommendation of Micro-videoYinwei Wei, Xiang Wang, Liqiang Nie, Xiangnan He, Richang Hong & Tat-Seng ChuaIn 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 NetworkLixi Deng, Jingjing Chen, Qianru Sun, Xiangnan He, Sheng Tang, Zhaoyan Ming, Yongdong Zhang & Tat-Seng ChuaIn 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 SourcesFrancesco Gelli, Tiberio Uricchio, Xiangnan He, Alberto Del Bimbo & Tat-Seng ChuaIn 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 DataJingtao Ding, Yuhan Quan, Xiangnan He, Yong Li & Depeng JinIn 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 RecommendationXin Xin, Bo Chen, Xiangnan He, Dong Wang, Yue Ding & Joemon JoseIn 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 NetworkLiang Chen, Yang Liu, Xiangnan He, Lianli Gao & Zibin ZhengIn 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 TrainingFuli Feng, Huimin Chen, Xiangnan He*, Maosong Sun, Tat-Seng Chua & Ji DingIn 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 NetworksWeijian Chen, Yulong Gu, Zhaochun Ren*, Xiangnan He*, Hongtao Xie, Tong Guo, Dawei Yin & Yongdong ZhangIn 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 PreferenceYixin Cao, Xiang Wang, Xiangnan He*, Zikun Hu & Tat-Seng ChuaIn 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 DataChen Gao, Xiangning Chen, Fuli Feng, Kai Zhao, Xiangnan He, Yong Li & Depeng JinIn 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 RecommendationXiang Wang, Dingxian Wang, Canran Xu, Xiangnan He, Yixin Cao & Tat-Seng ChuaIn 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 AnsweringXiangpeng Li, Jingkuan Song, Lianli Gao, Xianglong Liu, Wenbing Huang, Chuang Gan & Xiangnan HeIn 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 RecommendationFajie Yuan, Alexandros Karatzoglou, Ioannis Arapakis, Joemon M. Jose & Xiangnan HeProceedings 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 DataChen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li, Tat-Seng Chua & Depeng JinIn 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 RecommendationXiangnan 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 RecommendationDa 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 EmbeddingMing 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 HashingXin 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 VideosMeng 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 WhatXuemeng 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 FilteringXiangnan 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 DataJingtao 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 RecommendationHan 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 PredictionZhiyong 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 MediaTiancheng 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 BGDFajie 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 RecommendationXiang 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 HypergraphsFuli 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 DataJingtao 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 SamplesXin 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 ArchitecturesWenqiang 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 LBSNsJingyuan 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 ResolutionDongxiang 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 RetrievalZan 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 AnalyticsXiangnan 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 UsersXiang 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 ItemsDa 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 AttentionJingyuan 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 FilteringXiangnan 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 FeedbackImmanuel 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 ImagesFrancesco 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 SoundsLiqiang 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 LocalizationZhenguang 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 MotionDejing 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 MediaLizi 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 RecognitionWenqiang 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 FeedbackXiangnan 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 FilteringHanwang 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 RecommendationTao 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-VideoJianglong 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 AspectsXiangnan 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 ImagesTao 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 DisseminationXiao 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 ItemsXiangnan 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 AnthologyYiping 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] Learning Vertex Representations for Bipartite NetworksMing Gao, Xiangnan He, Leihui Chen, Tingting Liu, Jinglin Zhang Aoying ZhouIEEE Transactions on Knowledge and Data Engineering (TKDE 2020).   PDF   Codes

[2] Learning Visual Elements of Images for Discovery of Brand Posts. Francesco GelliTiberio Uricchio*, Xiangnan He*, Alberto Del Bimbo & Tat-Seng Chua, IEEE Transactions on Multimedia Computing Communications and Applications (TOMM 2020).   PDF    *Corresponding author

[3] Graph Adversarial Training: Dynamically Regularizing Based on Graph StructureFuli Feng, Xiangnan He*, Jie Tang & Tat-Seng Chua, IEEE Transactions on Knowledge and Data Engineering (TKDE 2020).   PDF    Codes   *Corresponding author

[4] Learning to Recommend with Multiple Cascading BehaviorsChen Gao, Xiangnan He, Dahua Gan, Xiangning Chen, Fuli Feng, Yong Li & Tat-Seng Chua, IEEE Transactions on Knowledge and Data Engineering (TKDE 2020).    PDF

[5] Improving Implicit Recommender Systems with Auxiliary DataJingtao Ding, Guanghui Yu, Yong Li, Xiangnan He, & Depeng Jin, ACM Transactions on Information Systems (TOIS 2020).   PDF  

[6] ATM: An Attentive Translation Model for Next-Item RecommendationBin Wu, Xiangnan He, Zhongchuan Sun, Liang Chen & Yangdong Ye, IEEE Transactions on Industrial Informatics (TII 2020).   PDF

[7] Social-enhanced Attentive Group RecommendationDa Cao, Xiangnan He, Lianhai Miao, Guangyi Xiao, Hao Chen & Richang HongIEEE Transactions on Knowledge and Data Engineering (TKDE 2019).  PDF 

[8] Knowledge Embedding Based Topic Model for Multi-modal Social Event AnalysisFeng Xue, Richang Hong, Xiangnan He, Jianwei Wang, Shengsheng Qian, Tianzhu Zhang & Changsheng XuIEEE Transactions on Multimedia (TMM 2019).   PDF  

[9] Graph Adversarial Training: Dynamically Regularizing Based on Graph StructureFuli Feng, Xiangnan He*, Jie Tang, & Tat-Seng ChuaIEEE Transactions on Knowledge and Data Engineering (TKDE, major revision).   PDF  

[10] Learning Vertex Representations for Bipartite NetworksMing Gao, Xiangnan He*, Leihui Chen, Aoying ZhouIEEE Transactions on Knowledge and Data Engineering.   PDF  *Corresponding author

[11] Hierarchical Attention Network for Visually-aware Food RecommendationXiaoyan Gao, Fuli Feng, Xiangnan He, Heyan Huang, Xinyu Guan, Chong Feng, Zhaoyan Ming, Tat-Seng ChuaIEEE Transactions on Multimedia (TMM).    PDF 

[12] Learning to Compose and Reason with Language Tree Structures for Visual GroundingRichang Hong, Daqing Liu, Xiaoyu Mo, Xiangnan He & Hanwang ZhangIEEE Transactions on Pattern Recognition and Machine Intelligence (TPAMI 2019).   PDF  

[13] Modeling Embedding Dimension Correlations via Convolutional Neural Collaborative FilteringXiaoyu Du, Xiangnan He*, Fajie Yuan, Jinhui Tang, Zhiguang Qin & Tat-Seng ChuaACM Transactions on Information Systems (TOIS 2019).   PDF    Codes   *Corresponding author

[14] Temporal Relational Ranking for Stock PredictionFuli Feng, Xiangnan He*, Xiang Wang, Cheng Luo, Yiqun Liu & Tat-Seng ChuaACM Transactions on Information Systems (TOIS 2019).  PDF   Codes   *Corresponding author

[15] Attentive Aspect Modeling for Review-aware RecommendationXinyu Guan, Zhiyong Cheng, Xiangnan He, Yongfeng Zhang, Zhibo Zhu, Qinke Peng & Tat-Seng ChuaACM Transactions on Information Systems (TOIS 2019).   PDF   Codes 

[16] Fast Matrix Factorization with Non-Uniform Weights on Missing DataXiangnan He, Jinhui Tang, Xiaoyu Du, Richang Hong, Tongwei Ren & Tat-Seng ChuaIEEE Transactions on Neural Networks and Learning Systems.   PDF   Codes  

[17] Adversarial Training Towards Robust Multimedia Recommender SystemJinhui Tang, Xiaoyu Du, Xiangnan He*, Fajie Yuan, Qi Tian & Tat-Seng ChuaIEEE Transactions on Knowledge and Data Engineering (TKDE 2019).    PDF   Codes   *Corresponding author

[18] Sampler Design for Bayesian Personalized Ranking by Leveraging View DataJingtao Ding, Guanghui Yu, Xiangnan He, Fuli Feng, Yong Li & Depeng JinIEEE Transactions on Knowledge and Data Engineering (TKDE 2019).   PDF  

[19] Generative Adversarial Active Learning for Unsupervised Outlier DetectionYezheng 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

[20] Deep Item-based Collaborative Filtering for Top-N RecommendationFeng Xue, Xiangnan He*, Xiang Wang, Jiandong Xu, Kai Liu & Richang HongACM Transactions on Information Systems (TOIS 2019).  PDF  Codes *Corresponding author 

[21] HoAFM: A High-order Attentive Factorization Machine for CTR PredictionZhulin Tao, Xiang Wang, Xiangnan He, Xianglin Huang & Tat-Seng ChuaInformation Processing & Management (IPM 2019).  PDF 

[22] Attributed Social Network EmbeddingLizi 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  

[23] NAIS: Neural Attentive Item Similarity Model for RecommendationXiangnan 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  

[24] BiRank: Towards Ranking on Bipartite GraphsXiangnan 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

[25] Cross-Platform App Recommendation by Jointly Modeling Ratings and TextsDa 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 

[26] Discrete Multi-modal Hashing with Canonical Views for Robust Mobile Landmark SearchLei 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  

[27] Version-sensitive mobile App recommendationDa 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

[28] A Truthful Incentive Mechanism for Online Recruitment in Mobile Crowd Sensing SystemXiao Chen, Min Liu, Yaqin Zhou, Zhongcheng Li, Shuang Chen, Xiangnan He (2017). Sensors, 17(1):79.  PDF 








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