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Journal Papers (1 Nature Communications, 21 TKDE, 1 PIEEE, 8 TOIS, 1 TPAMI, 1 TMC, 3 TNNLS, 3 TKDD, 3 T. Cybernetics, 2 TMM, 1 The Innovation)

    2025

  1. Yiqing Wu, Ruobing Xie, Zhao Zhang, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Zhulin An, Yongjun Xu.: ID-centric pre-training for recommendation. TOIS 2025.

  2. Yiqi Tong, Jiarui Zhang, Shaohang Wei, Wei Guo, Fuzhen Zhuang*, Deqing Wang, Xi Yang, Richeng Xuan.: MindScore: quantifying human preference for text-to-image generation through multi-view lens. SCIS 2025.

  3. Zhanpeng Guan, Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang, Fei Wang, Zhulin An, Yongjun Xu.: AdaE: Knowledge Graph Embedding with Adaptive Embedding Sizes. TKDE 2025.

  4. Meng Yuan, Zhao Zhang, Wei Chen, Chu Zhao, Tong Cai, Deqing Wang, Rui Liu, Fuzhen Zhuang*.: HEK-CL: Hierarchical Enhanced Knowledge-Aware Contrastive Learning for Recommendation. TOIS 2025.

  5. Yiqi Tong, Qianqi Liu, Wei Guo, Hongrui Niu, Fuzhen Zhuang*, Deqing Wang, Jun Gao.: PCRec: A Multi-Interest News Recommendation Framework with PromptGuided Cross-view Contrastive Learning. JCST 2025.

  6. Hangtong Xu, Yuanbo Xu, Chaozhuo Li, Fuzhen Zhuang.: Causal Structure Representation Learning of Unobserved Confounders in Latent Space for Recommendation. TOIS 2025.

  7. Chuan Qin, Chuyu Fang, Kaichun Yao, Xi Chen, Fuzhen Zhuang, Hengshu Zhu.: COTR: Efficient Job Task Recognition for Occupational Information Systems with Class-Incremental Learning. TMIS 2025.

    8. 2024

  8. Ying Sun, Yang Ji, Hengshu Zhu, Fuzhen Zhuang, Qing He, Hui Xiong.: Market-aware Long-term Job Skill Recommendation with Explainable Deep Reinforcement Learning. TOIS 2024.

  9. Yuanbo Xu, Fuzhen Zhuang, En Wang, Chaozhuo Li, Jie Wu.: Learning without Missing-At-Random Prior Propensity-A Generative Approach for Recommender Systems. TKDE 2024.

  10. Xiao Zhang, Shuqing Xu, Huashan Chen, Zekai Chen, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu.: Rethinking Robust Multivariate Time Series Anomaly Detection: A Hierarchical Spatio-Temporal Variational Perspective. TKDE 2024.

  11. Yiheng Jiang, Yuanbo Xu, Yongjian Yang, Funing Yang, Pengyang Wang, Chaozhuo Li, Fuzhen Zhuang, Hui Xiong.: TriMLP: A Foundational MLP-like Architecture for Sequential Recommendation. TOIS 2024.

  12. Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang*, Yu Zhao, Deqing Wang, Hongwei Zheng.: Temporal Knowledge Graph Reasoning with Dynamic Memory Enhancement. TKDE 2024.

  13. Chunlai Dong, Haochao Ying*, Renjun Hu, Yuyang Xu, Jintai Chen, Fuzhen Zhuang, Jian Wu.: A Progressively-Passing-then-Disentangling Approach to Recipe Recommendation. TMM 2024.

  14. Huishi Luo, Fuzhen Zhuang*, Ruobing Xie, Hengshu Zhu, Deqing Wang, Zhulin An, Yongjun Xu.: A survey on causal inference for recommendation. The Innovation 2024.

  15. Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang*, Xu Zhang, Leyu Lin, Qing He.: Personalized Prompt for Sequential Recommendation. TKDE 2024.

  16. Shaopeng Wei, Jia Lv, Yu Guo, Qing Yang, Xingyan Chen, Yu Zhao, Qing Li, Fuzhen Zhuang, Gang Kou.: Combining intra-risk and contagion risk for enterprise bankruptcy prediction using graph neural networks. Information Sciences 2024.

    17. 2023

  17. Wei Chen, Yiqing Wu, Zhao Zhang, Fuzhen Zhuang*, Zhongshi He, Ruobin Xie, Feng Xia.: FairGap: Fairness-aware Recommendation via Generating Counterfactual Graph. TOIS 2023.

  18. Ying Luo, Guoliang Kang, Kexin Liu, Fuzhen Zhuang, Jinhu Lv.: Taking a Closer Look at Factor Disentanglement: Dual-Path Variational Autoencoder Learning for Domain Generalization. TMM 2023.

  19. Yuting Zhang, Ying Sun, Fuzhen Zhuang*, Yongchun Zhu, Zhulin An, Yongjun Xu.: Triple Dual Learning for Opinion-Based Explainable Recommendation. TOIS 2023.

  20. Tao Zou, Le Yu, Leilei Sun, Bowen Du, Deqing Wang, Fuzhen Zhuang.: Event-based Dynamic Graph Representation Learning for Patent Application Trend Prediction. TKDE 2023.

  21. Chuanguang Yang, Zhulin An, Helong Zhou, Fuzhen Zhuang, Yongjun Xu, Qian Zhang.: Online Knowledge Distillation via Mutual Contrastive Learning for Visual Recognition. TPAMI 2023.

    22. 2022

  22. Qiming Li, Zhao Zhang, Fuzhen Zhuang, Yongjun Xu, Chao Li.: Topic-aware Intention Network for Explainable Recommendation with Knowledge Enhancement. TOIS 2022.

  23. Yu Zhao, Shaopeng Wei, Huaming Du, Xingyan Chen, Qing Li, Fuzhen Zhuang, Ji Liu, Kang Kou.: Learning Bi-typed Multi-relational Heterogeneous Graph via Dual Hierarchical Attention Networks. TKDE 2022.

  24. Yu Zhao, Huaming Du, Ying Liu, Shaopeng Wei, Xingyan Chen, Fuzhen Zhuang, Qing Li, Gang Kou.: Stock Movement Prediction Based on Bi-typed Hybrid-relational Market Knowledge Graph via Dual Attention Networks. TKDE 2022.

  25. Hao Liu, Qingyu Guo, Hengshu Zhu, Yanjie Fu, Fuzhen Zhuang, Xiaojuan Ma, Hui Xiong.: Characterizing and Forecasting Urban Vibrancy Evolution: A Multi-View Graph Mining Perspective. TKDD 2022.

  26. Shuokai Li, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Zhenwei Tang, Wayne Xin Zhao, Qing He.: Self-Supervised Learning for Conversational Recommendation. Information Processing and Management 2022.

  27. Yongchun Zhu, Qiang Sheng, Juan Cao, Qiong Nan, Kai Shu, Minghui Wu, Jindong Wang, Fuzhen Zhuang.: Memory-Guided Multi-View Multi-Domain Fake News Detection. TKDE 2022.

  28. Yiqi Tong, Fuzhen Zhuang*, Huajie Zhang, Chuyu Fang, Yu Zhao, Deqing Wang, Hengshu Zhu, Bin Ni.: Improving Biomedical Named Entity Recognition by Dynamic Caching Inter-sentence Information. Bioinformatics 2022.

  29. Yuyang Xu, Haochao Ying, Siyi Qian, Fuzhen Zhuang, Xiao Zhang, Deqing Wang, Jian Wu, Hui Xiong.: Time-aware Context-Gated Graph Attention Network for Clinical Risk Prediction. TKDE 2022.

  30. Tianxin Wang, Fuzhen Zhuang*, Ying Sun, Xiangliang Zhang, Leyu Lin, Feng Xia, Lei He, Qing He.: Adaptively Sharing Multi-Levels of Distributed Representations in Multi-Task Learning. Information Sciences 2022.

  31. Hao Liu, Qingyu Guo, Hengshu Zhu, Fuzhen Zhuang, Shenwen Yang, Dejing Dou, Hui Xiong.: Who will Win the Data Science Competition? Insights from KDD Cup 2019 and Beyond. TKDD 2022.

  32. Yu Zhao, Han Zhou, Anxiang Zhang, Ruobing Xie, Qing Li, Fuzhen Zhuang*.: Connecting Embeddings Based on Multiplex Relational Graph Attention Networks for Knowledge Graph Entity Typing. TKDE 2022.

    33. 2021

  33. Hongzheng Yu, Zekai Chen, Xiao Zhang, Xu Chen, Fuzhen Zhuang, Hui Xiong, Xiuzheng Chen.: FedHAR: Semi-Supervised Online Learning for Personalized Federated Human Activity Recognition. IEEE Transactions on Mobile Computing, 2021.

  34. Yu Zhao, Huali Feng, Han Zhou, Yanruo Yang, Xingyan Chen, Ruobing Xie, Fuzhen Zhuang, QingLi.: EIGAT: Incorporating global information in local attention for knowledge representation learning. Knowledge-Based Systems, 2021.

  35. Zhao Zhang, Fuzhen Zhuang*, Hengshu Zhu, Hui Xiong, Qing He.: Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning. TKDE 2021.

  36. Yongchun Zhu, Fuzhen Zhuang*, Xiangliang Zhang, Zhiyuan Qi, Zhiping Shi, Juan Cao, Qing He.: Combat Data Shift in Few-shot Learning with Knowledge Graph. Frontiers of Computer Science 2021.

  37. Ying Sun, Fuzhen Zhuang*, Hengshu Zhu, Xin Song, Qing He, Hui Xiong.: Modeling the Impact of Person-Organization Fit on Talent Management with Structure-Aware Attentive Neural Networks. TKDE 2021.

  38. Ying Sun, Fuzhen Zhuang*, Hengshu Zhu*, Qi Zhang, Qing He, Hui Xiong*.: Market-oriented Job Skill Valuation with Cooperative Composition Neural Network. Nature Communications, 2021.

  39. Zhao Zhang, Fuzhen Zhuang*, Meng Qu, Zhengyu Niu, Hui Xiong, Qing He.: Knowledge Graph Embedding with Shared Latent Semantic Units. Neural Networks, 2021.

  40. Xiao Zhang, Hongzheng Yu, Yang Yang, Jingjing Gu, Yujun Li, Fuzhen Zhuang, Dongxiao Yu, Zhaochun Ren.: HarMI: Human Activity Recognition via Multi-modality Incremental Learning. IEEE Journal of Biomedical and Health Informatics, 2021.

    2020

  41. Xiaowei Zhao, Deqing Wang, Zhengyang Zhao, Wei Liu, Chenwei Lu, Fuzhen Zhuang.: A Neural Topic Model with Word Vectors and Entity Vectors for Short Texts. Information Processing & Management, 2020.

  42. Yuanbo Xu, Yongjian Yang, En Wang, Fuzhen Zhuang, Hui Xiong.: Detect Professional Malicious User with Metric Learning in Recommender Systems. IEEE TKDE, 2020.

  43. Chengfeng Xu, Feng Jian, Pengpeng Zhao, Fuzhen Zhuang, Deqing Wang, Yanchi Liu, Victor S. Sheng.: Long- and Short-Term Self-Attention Network for Sequential Recommendation. Neurocomputing, 2020.

  44. Qingyu Guo, Fuzhen Zhuang*, Chuan Qin, Hengshu Zhu, Xing Xie, Hui Xiong, Qing He: A Survey on Knowledge Graph-Based Recommender Systems. IEEE TKDE, 2020.

  45. Dongbo Xi, Fuzhen Zhuang*, Yanchi Liu, Hengshu Zhu, Pengpeng Zhao, Chang Tan, Qing He: Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification. Neural Networks, 2020.

  46. Zhicheng He, Jie Liu, Kai Dang, Fuzhen Zhuang, Yalou Huang: Leveraging Maximum Entropy and Correlation on Latent Factors for Learning Representations. Neural Networks, 2020.

  47. Pengpeng Zhao, Anjing Luo, Yanchi Liu, Jiajie Xu, Zhixu Li, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou: Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation. IEEE TKDE, 2020.

  48. Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He: A Comprehensive Survey on Transfer Learning. Proceedings of IEEE, 2020.

  49. Haochao Ying, Qingyu Song, Jintai Chen, Tingting Liang, Jingjing Gu, Fuzhen Zhuang, Danny Z Chen, Jian Wu: A Semi-supervised Deep Convolutional Framework for Signet Ring Cell Detection. Neurocomputing, 2020.

  50. Yuanbo Xu, Yongjian Yang, En Wang, Jiayu Han, Fuzhen Zhuang, Zhiwen Yu, Hui Xiong: Neural Serendipity Recommendation: Exploring the Balance between Accuracy and Novelty with sparse Explicit Feedback. ACM Transactions on Knowledge Discovery from Data, 2020.

  51. Yongchun Zhu, Fuzhen Zhuang*, Jindong Wang, Guolin Ke, Jingwu Chen, Jiang Bian, Hui Xiong, Qing He: Deep Subdomain Adaptation Network for Image Classification. IEEE Transactions on Neural Networks and Learning Systems, 2020.

  52. Jingjing Gu, Qiang Zhou, Jingyuan Yang, Yanchi Liu, Fuzhen Zhuang, Yanchao Zhao, and Hui Xiong: Exploiting Interpretable Patterns for Flow Prediction in Dockless Bike Sharing Systems. IEEE TKDE, 2020.

  53. Jingjing Gu , Cheng Liu, Yi Zhuang, Xiaojiang Du, Fuzhen Zhuang, Haochao Ying, Yanchao Zhao, and Mohsen Guizani: Dynamic Measurement and Data Calibration for Aerial Mobile IoT. IEEE Internet of Things, 2020.

  54. Hengshu Zhu, Ying Sun, Wenjia Zhao, Fuzhen Zhuang, Baoshan Wang, Hui Xiong: Rapid Learning of Earthquake Felt Area and Intensity Distribution with Real-time Search Engine Queries. Scientific Reports, 2020.

  55. Deqing Wang, Baoyu Jing, Chenwei Lu, Junjie Wu, Guannan Liu, Chenguang Du, Fuzhen Zhuang*: Coarse Alignment of Topic and Sentiment: A Unified Model for Cross-Lingual Sentiment Classification. IEEE Transactions on Neural Networks and Learning Systems, 2020.

  56. Fuzhen Zhuang, Yingmin Zhou, Haochao Ying, Fuzheng Zhang, Xiang Ao, Xing Xie, Qing He, Hui Xiong: Sequential Recommendation via Cross-domain Novelty Seeking Trait Mining. Journal of Computer Science and Technology, 2020.

  57. Xiaoyi Deng, Yenchun Jim Wu, Fuzhen Zhuang: Trust-embedded collaborative deep generative model for social recommendation. The Journal of Supercomputing, 2020.

  58. Jia He, Changying Du, Fuzhen Zhuang, Xin Yin, Qing He, Guoping Long: Online Bayesian max-margin subspace learning for multi-view classification and regression. Mach. Learn. 109(2): 219-249 (2020).

  59. Jiayu Han, Lei Zheng, Yuanbo Xu, Bangzuo Zhang, Fuzhen Zhuang, Philip Yu, Wanli Zuo: Adaptive Deep Modeling of Users and Items Using Side Information for Recommendation. IEEE Trans. Neural Networks Learn. Syst. 31(3): 737-748 (2020).

    60. 2019

  60. Jingwu Chen, Fuzhen Zhuang*, Tianxin Wang, Leyu Lin, Feng Xia, Lihuan Du, Qing He: Follow the Title then Read the Article: Click-guide Network for Dwell Time Prediction. IEEE TKDE, 2019.

  61. Deqing Wang, Chenwei Lu, Junjie Wu, Hongfu Liu, Wenjie Zhang, Fuzhen Zhuang, Hui Zhang: Softly Associative Transfer Learning for Cross-domain Classification. IEEE Transactions on Cybernetics, 2019.

  62. Xiaoyi Deng, Fuzhen Zhuang, Zhiguo Zhu: Neural variational collaborative filtering with side information for top-K recommendation. Int. J. Machine Learning & Cybernetics 10(11): 3273-3284 (2019).

  63. Yongchun Zhu, Fuzhen Zhuang*, Jindong Wang, Jingwu Chen, Zhiping Shi, Wenjuan Wu, Qing He: Multi-representation adaptation network for cross-domain image classification. Neural Networks 119: 214-221 (2019).

  64. Jia He, Fuzhen Zhuang*, Yanchi Liu, Qing He, Fen Lin: Bayesian dual neural networks for recommendation. Frontiers Comput. Sci. 13(6): 1255-1265(2019).

  65. Ming Huang, Fuzhen Zhuang*, Xiao Zhang, Xiang Ao, Zhengyu Niu, Min-Ling Zhang, Qing He: Supervised representation learning for multi-label classification. Machine Learning 108(5): 747-763 (2019).

  66. Thapana Boonchoo, Xiang Ao, Yang Liu, Weizhong Zhao, Fuzhen Zhuang, Qing He: Grid-based DBSCAN: Indexing and inference. Pattern Recognition 90: 271-284 (2019).

  67. Yuanbo Xu , Yongjian Yang , Jiayu Han , En Wang , Fuzhen Zhuang , Jingyuan Yang , Hui Xiong : NeuO: Exploiting the sentimental bias between ratings and reviews with neural networks. Neural Networks 111 : 77-88 ( 2019 ).

  68. Zhao Zhang , Fuzhen Zhuang* , Xuebing Li , Zheng-Yu Niu , Jia He , Qing He , Hui Xiong : Knowledge triple mining via multi-task learning. Inf. Syst. 80 : 64-75 ( 2019 ).

    69. 2018

  69. Fuzhen Zhuang , Jing Zheng , Jingwu Chen , Xiangliang Zhang , Chuan Shi , Qing He : Transfer collaborative filtering from multiple sources via consensus regularization. Neural Networks 108 : 287-295 ( 2018 ).

  70. Ding Xiao , Yugang Ji , Yitong Li , Fuzhen Zhuang , Chuan Shi : Coupled matrix factorization and topic modeling for aspect mining. Inf. Process. Manage. 54 ( 6 ) : 861-873 ( 2018 ).

  71. Xiang Ao , Ping Luo , Chengkai Li , Fuzhen Zhuang , Qing He : Discovering and learning sensational episodes of news events. Inf. Syst. 78 : 68-80 ( 2018 ) .

  72. Yangli-ao Geng , Qingyong Li , Rong Zheng , Fuzhen Zhuang , Ruisi He , Naixue Xiong : RECOME: A new density-based clustering algorithm using relative KNN kernel density. Inf. Sci. 436-437 : 13-30 ( 2018 ) .

  73. Xiang Ao , Ping Luo , Jin Wang , Fuzhen Zhuang , Qing He : Mining Precise-Positioning Episode Rules from Event Sequences. IEEE TKDE. 30 ( 3 ) : 530-543 ( 2018 ).

  74. Fuzhen Zhuang , Xuebing Li , Xin Jin , Dapeng Zhang , Lirong Qiu , Qing He : Semantic Feature Learning for Heterogeneous Multitask Classification via Non-Negative Matrix Factorization. IEEE Trans. Cybernetics 48 ( 8 ) : 2284-2293 ( 2018 ). PDF

  75. Fuzhen Zhuang , Xiaohu Cheng , Ping Luo , Sinno Jialin Pan , Qing He : Supervised Representation Learning with Double Encoding-Layer Autoencoder for Transfer Learning. ACM TIST 9 ( 2 ) : 16:1-16:17 ( 2018 ). PDF

  76. Ning Li , Wenjuan Luo , Kun Yang , Fuzhen Zhuang , Qing He , Zhongzhi Shi : Self-organizing weighted incremental probabilistic latent semantic analysis. Int. J. Machine Learning & Cybernetics 9 ( 12 ) : 1987-1998 ( 2018 ).

    77. 2017

  77. Fuzhen Zhuang, Zhiqiang Zhang , Mingda Qian , Chuan Shi , Xing Xie , Qing He : Representation learning via Dual-Autoencoder for recommendation. Neural Networks 90 : 83-89 (2017). PDF

  78. Jing Zheng , Jian Liu , Chuan Shi , Fuzhen Zhuang , Jingzhi Li , Bin Wu : Recommendation in heterogeneous information network via dual similarity regularization. I. J. Data Science and Analytics 3 ( 1 ) : 35-48 ( 2017 ) .PDF

    79. 2016

  79. Chuan Shi , Jian Liu , Fuzhen Zhuang* , Philip S. Yu , Bin Wu : Integrating heterogeneous information via flexible regularization framework for recommendation. Knowl. Inf. Syst. 49 ( 3 ) : 835-859 ( 2016 ). PDF

  80. Haocheng Wang , Fuzhen Zhuang , Xin Jin , Xiang Ao , Qing He : Bag of little bootstraps on features for enhancing classification performance. Intell. Data Anal. 20 ( 5 ) : 1085-1099 ( 2016 ). PDF

    81. 2015

  81. Shuhui Wang , Fuzhen Zhuang , Shuqiang Jiang , Qingming Huang , Qi Tian : Cluster-sensitive Structured Correlation Analysis for Web cross-modal retrieval. Neurocomputing 168 : 747-760 ( 2015 ). PDF

  82. Wenjuan Luo, Fuzhen Zhuang, Weizhong Zhao, Qing He, Zhongzhi Shi: QPLSA: Utilizing quadtuples for aspect identification and rating. Inf. Process. Manage. 51(1): 25-41 (2015). PDF

  83. Wenchao Yu, Fuzhen Zhuang, Qing He, Zhongzhi Shi: Learning deep representations via extreme learning machines. Neurocomputing 149 : 308-315 (2015). PDF

  84. Qing He, Haocheng Wang, Fuzhen Zhuang, Tianfeng Shang, Zhongzhi Shi: Parallel sampling from big data with uncertainty distribution. Fuzzy Sets and Systems 258 : 117-133 (2015). PDF

    85. 2014

  85. Fuzhen Zhuang, Ping Luo, Changying Du, Qing He, Zhongzhi Shi, Hui Xiong: Triplex Transfer Learning: Exploiting Both Shared and Distinct Concepts for Text Classification. IEEE T. Cybernetics 44 (7): 1191-1203 (2014). PDF

  86. Xiang Ao, Ping Luo, Xudong Ma, Fuzhen Zhuang, Qing He, Zhongzhi Shi, Zhiyong Shen: Combining supervised and unsupervised models via unconstrained probabilistic embedding. Inf. Sci. 257 : 101-114 (2014). PDF

  87. Shuo Han, Fuzhen Zhuang, Qing He, Zhongzhi Shi, Xiang Ao: Energy Model for Rumor Propagation on Social Networks. Physica A: Statistical Mechanics and its Applications, 394: 99-109 (2014). PDF

  88. Qing He, Xin Jin, Changying Du, Fuzhen Zhuang, Zhongzhi Shi: Clustering in Extreme Learning Machine Feature Space. Neurocomputing, 2014. PDF

    89. 2013

  89. Wenjuan Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi. Exploiting relevance, coverage, and novelty for query-focused multi-document summarization. Knowledge-based Systems. pp.33-42, 2013. PDF

  90. Qing He, Tianfeng Shang, Fuzhen Zhuang, Zhongzhi Shi. “Parallel Extreme Learning Machine for Regression based on MapReduce”. Neurocomputing, pp.52-58, 2013. PDF

  91. Xin Jin, Yongquan Liang, Dongping Tian, Fuzhen Zhuang. Particle swarm optimization using dimension selection methods. Applied Mathematics and Computation, pp.5185-5197, 2013. PDF

    92. 2012

  92. Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi, Hui Xiong. “Mining Distinction and Commonality across Multiple Domains using Generative Model for Text Classification”. IEEE TKDE , pp.2025-2039, 2012. PDF

  93. Fuzhen Zhuang, George Karypis, Xia Ning, Qing He, Zhongzhi Shi.: Multi-view Learning via Probabilistic Latent Semantic Analysis. Information Sciences, pp.20-30, 2012. PDF

  94. Shengmei Luo, Qing He, Lixia Liu, Xiang Ao, Ning Li, Fuzhen Zhuang: Parallel Web Mining System Based on Cloud Platform. ZTE Communications, 10(4): 45-53 (2012). PDF

    95. 2011 and Before

  95. Fuzhen Zhuang, Ping Luo, Hui Xiong, Qing He, Yuhong Xiong, Zhongzhi Shi. “Exploiting Associations between Word Clusters and Document Classes for Cross-domain Text Categorization”. Statistical Analysis and Data Mining, Wiley, pp.100-114, 2011. PDF

  96. Qing He, Changying Du, Qun Wang, Fuzhen Zhuang, Zhongzhi Shi. A parallel incremental extreme SVM classifier. Neurocomputing, pp.2532-2540, 2011. PDF

  97. Fuzhen Zhuang, Ping Luo, Hui Xiong, Yuhong Xiong, Qing He, Zhongzhi Shi. “Cross-domain Learning From Multiple Sources: A Consensus Regularization Perspective”. IEEE TKDE , 2010, 22(12), pp. 1664–1678. PDF

  98. Zhuang Fuzhen, Luo Ping, He Qing, Shi Zhongzhi. “Inductive Transfer Learning for Unlabeled Target-domain via Hybrid Regularization”. Chinese Science Bulletin, 2009, 54(14): 2470–2478. PDF

Conference Papers (16 KDD, 13 IJCAI, 14 AAAI, 11 WWW, 16 SIGIR, 4 ICDE, 3 NeurIPS, 3 ACL, 2 MM)

    2025

  1. Fuwei Zhang, Xiaoyu Liu, Jia Xinyu, Yingfei Zhang, Zenghua Xia, Fei Jiang, Wei Lin, Fuzhen Zhuang*, Zhao Zhang.: HierGR: Hierarchical Semantic Representation Enhancement for Generative Retrieval in Food Delivery Search. ACL 2025 Industry Track.

  2. Wei Chen, Zhao Zhang, Meng Yuan, Kepeng Xu, Fuzhen Zhuang*.: FCKT: Fine-Grained Cross-Task Knowledge Transfer with Semantic Contrastive Learning for Targeted Sentiment Analysis. IJCAI 2025.

  3. Huishi Luo, Yiqing Wu, Yiwen Chen, Fuzhen Zhuang*, Deqing Wang.: CDC: Causal Domain Clustering for Multi-Domain Recommendation. SIGIR 2025.

  4. Jing Fan, Chen Zhu, Han Wu, Fuzhen Zhuang*, Deqing Wang, Hengshu Zhu.: Improving Multi-Attribute Fairness in LLM-Based Recommenders through a Mixture-of-Experts Contrastive Learning Method. DASFAA 2025.

  5. Zheng Dou, Deqing Wang, Fuzhen Zhuang, Jian Ren, Yanlin Hu.: FLeW: Facet-Level and Adaptive Weighted Representation Learning of Scientific Documents. DASFAA 2025 (Short).

  6. Meng Yuan, Yutian Xiao, Wei Chen, Chu Zhao, Deqing Wang, Fuzhen Zhuang*.: Hyperbolic Diffusion Recommender Model. TheWebConf 2025.

  7. Xiaoyu Liu, Yiqing Wu, Dingyuan Zhu, Yifan Wu, Daixin Wang, Xiaobo Qin, Fuzhen Zhuang*.: Whitening-based Adversarial Bi-Regressor for Cross-platform Insurance Claims Prediction. TheWebConf 2025 (Short).

  8. Wei Chen, Guo Ye, Yakun Wang, Zhao Zhang, Libang Zhang, Daixin Wang, Zhiqiang Zhang, Fuzhen Zhuang*.: Smoothness Really Matters: A Simple yet Effective Approach for Unsupervised Graph Domain Adaptation. AAAI 2025.

  9. Yuxiao Gao, Fuwei Zhang, Zhao Zhang, Xiaoshuang Min, Fuzhen Zhuang*.: Mixed-Curvature Multi-Modal Knowledge Graph Completion. AAAI 2025.

  10. Huishi Luo, YiWen Chen, Yiqing Wu, Fuzhen Zhuang*, deqing wang.: One for Dozens: Adaptive REcommendation for All Domains with Counterfactual Augmentation. AAAI 2025.

    11. 2024

  11. Xi Chen, Chuan Qin, Chuyu Fang, Chao Wang, Chen Zhu, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong.: Job-SDF: A Multi-Granularity Dataset for Job Skill Demand Forecasting and Benchmarking. NeurIPS 2024.

  12. Mingyi Li, Xiao Zhang, Qi Wang, Tengfei LIU, Ruofan Wu, Weiqiang Wang, Fuzhen Zhuang, Hui Xiong, Dongxiao Yu.: Resource-Aware Federated Self-Supervised Learning with Global Class Representations. NeurIPS 2024.

  13. Ting Jiang, Shaohan Huang, Zhongzhi Luan, deqing wang, Fuzhen Zhuang.: Scaling Sentence Embeddings with Large Language Models. EMNLP 2024 Findings.

  14. Yongjing Hao, Fuzhen Zhuang, Deqing Wang, Guanfeng Liu, Victor S. Sheng and Pengpeng Zhao.: A General Strategy Graph Collaborative Filtering for Recommendation Unlearning. CIKM 2024.

  15. Caijun Xu, Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang*, Rui Liu.: Exploring High-Order User Preference with Knowledge Graph for Recommendation. CIKM 2024 (Short).

  16. Fuwei Zhang, Zhao Zhang, Fuzhen Zhuang*, Zhiqiang Zhang, Jun Zhou and Deqing Wang.: Multi-view Temporal Knowledge Graph Reasoning. CIKM 2024 (Short).

  17. Yuting Zhang, Zhao Zhang, Yiqing Wu, Ying Sun, Fuzhen Zhuang*, Wenhui Yu, Lantao Hu, Han Li, Kun Gai, Zhulin An, Yongjun Xu.: Tag Tree-Guided Multi-grained Alignment for Multi-Domain Short Video Recommendation. ACM MM 2024.

  18. Yuting Zhang, Yiqing Wu, ruidong han, Ying Sun, Yongchun Zhu, Xiang Li, Wei Lin, Fuzhen Zhuang*, Zhulin An, Yongjun Xu.: Unified Dual-Intent Translation for Joint Modeling of Search and Recommendation. KDD 2024.

  19. Yanjie Gou, Yuanzhou Yao, Zhao Zhang, Yiqing Wu, Yi Hu, Fuzhen Zhuang, Jiangming Liu, Yongjun Xu.: Controllable Multi-Behavior Recommendation for In-Game Skins with Large Sequential Model. KDD 2024.

  20. Yiqing Wu, Ruobing Xie, Zhao Zhang, Xuonezhang, Fuzhen Zhuang, Leyu Lin, Zhanhui Kang, Yongjun Xu.: Dual-frequency Graph Neural Network for Sign-aware Recommendation. KDD 2024.

  21. Huaming Du, Long Shi, Xingyan Chen, Yu Zhao, Hegui Zhang, Carl Yang, Fuzhen Zhuang, Gang Kou.: Representation Learning of Temporal Graphs with Structural Roles. KDD 2024.

  22. Guanyu Jiang, Fuzhen Zhuang*, Bowen Song, Yongchun Zhu, Ying Sun, Weiqiang Wang, deqing wang. SeqSHAP: Subsequence Level Shapley Value Explanations for Sequential Predictions. DASFAA 2024.

  23. Feihu Jiang, Chuan Qin, Kaichun Yao, Chuyu Fang, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong.: Enhancing Question Answering for Enterprise Knowledge Bases using Large Language Models. DASFAA 2024.

  24. Yongjing Hao, Pengpeng Zhao, JIanfeng Qu, Lei Zhao, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou.: Meta-optimized Structural and Semantic Contrastive Learning for Graph Collaborative Filtering. ICDE 2024.

  25. Huajie Zhang, Ying Yuxin, Fuzhen Zhuang*, Haiqin Weng, Ying Sun, Zhao Zhang, Yiqi Tong, Yan Liu.: Multi-round counterfactual generation: interpreting and improving models of text classification. TheWebConf 2024 (Short).

  26. Chenguang Du, Hao Geng, Deqing Wang, Fuzhen Zhuang, Zhiqiang Zhang, Lanshan Zhang.: Exploiting Associations among Multi-Aspect Node Properties in Heterogeneous Graphs for Link Prediction. TheWebConf 2024 (Short).

  27. Meng Yuan, Fuwei Zhang, Yiqi Tong, Yuxin Ying, Fuzhen Zhuang, Deqing Wang, Baoxing Huai, Yi Zhang, jia su.: Light POI-Guided Conversational Recommder System based on Adaptive Space. SDM 2024.

  28. Wei Chen, YuXuan Liu, Zhao Zhang, Fuzhen Zhuang*, Jiang Zhong.: Modeling Adaptive Inter-Task Feature Interactions via Sentiment-Aware Contrastive Learning for Joint Aspect-Sentiment Prediction. AAAI 2024.

  29. Yongjing Hao, Pengpeng Zhao, Junhua Fang, Jianfeng Qu, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou.: Meta-optimized Joint Generative and Contrastive Learning for Sequential Recommendation. ICDE 2024.

  30. Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Guanfeng Liu, Fuzhen Zhuang, Victor S. Sheng.: Intent Contrastive Learning with Cross Subsequences for Sequential Recommendation. WSDM 2024.

    31. 2023

  31. Guanyu Jiang, Fuzhen Zhuang*, Bowen Song, Tianyi Zhang, Deqing Wang.: PriSHAP: Prior-guided Shapley Value Explanations for Correlated Features. CIKM 2023.

  32. Zhao Zhang, Fuwei Zhang, Fuzhen Zhuang*, Yongjun Xu.: Knowledge Graph Error Detection with Hierarchical Path Structure. CIKM 2023. (Best Short Paper)

  33. Zhenwei Tang, Shichao Pei, Xi Peng, Fuzhen Zhuang, Xiangliang Zhang, Robert Hoehndorf.: Neural Multi-hop Logical Query Answering with Concept-level Answers. ISWC 2023.

  34. Meng Yuan, Fuzhen Zhuang*, Zhao Zhang, Deqing Wang and Jin Dong.: Knowledge-based Multiple Adaptive Spaces Fusion for Recommendation. RecSys 2023.

  35. Yuting Zhang, Yiqing Wu, Ran Le, Yongchun Zhu, Fuzhen Zhuang*, Ruidong Han, Xiang Li, Wei Lin, Zhulin An, Yongjun Xu.: Modeling Dual Period-Varying Preferences for Takeaway Recommendation. KDD 2023. (ADS Track)

  36. Chuyu Fang, Chuan Qin, Qi Zhang, Kaichun Yao, Jingshuai Zhang, Hengshu Zhu, Fuzhen Zhuang*, Hui Xiong.: RecruitPro: A Pretrained Language Model with Skill-Aware Prompt Learning for Intelligent Recruitment. KDD 2023. (ADS Track)

  37. Zhao Zhang, Zhanpeng Guan, Fuwei Zhang, Fuzhen Zhuang*, Zhulin An, Fei Wang, Yongjun Xu.: Weighted Knowledge Graph Embedding. SIGIR 2023. (Full paper)

  38. Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong.: Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph. SIGIR 2023. (Full paper)

  39. Xiao Zhang, Ziming Ye, Jianfeng Lu, Fuzhen Zhuang, Yanwei Zheng, Dongxiao Yu.: Fine-Grained Preference-Aware Personalized Federated POI Recommendation with Data Sparsity. SIGIR 2023. (Full paper)

  40. Hanwen Du, Huanhuan Yuan, Pengpeng Zhao, Fuzhen Zhuang, Guanfeng Liu, Lei Zhao, Yanchi Liu, Victor S. Sheng.: Ensemble Modeling with Contrastive Knowledge Distillation for Sequential Recommendation. SIGIR 2023. (Full paper)

  41. Xiuyuan Qin, Huanhuan Yuan, Pengpeng Zhao, Junhua Fang, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, Victor Sheng.: Meta-optimized Contrastive Learning for Sequential Recommendation. SIGIR 2023. (Full paper)

  42. Xinyu Du, Huanhuan Yuan, Pengpeng Zhao, Jianfeng Qu, Fuzhen Zhuang, Guanfeng Liu, Yanchi Liu, Victor S Sheng.: Frequency Enhanced Hybrid Attention Network for Sequential Recommendation. SIGIR 2023. (Full paper)

  43. Shuokai Li, Jingbo Zhou, Jizhou Huang, Hao Chen, Fuzhen Zhuang, Qing H, Dejing Dou.: Matching Point of Interests and Travel Blog with Multi-view Information Fusion. SIGIR 2023. (Short paper)

  44. Yiqing Wu, Ruobing Xie, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Jie Zhou, Yongjun Xu, Qing He.: Attacking Pre-trained Recommendation. SIGIR 2023. (Short paper)

  45. Ting Jiang, Deqing wang, Fuzhen Zhuang, Ruobing Xie, Feng Xia.: Pruning Pre-trained Language Models Without Fine-Tuning. ACL 2023.

  46. Qingyu Guo, Fuzhen Zhuang*, Chuan Qin, Hengshu Zhu, Xing Xie, Hui Xiong, Qing He: A Survey on Knowledge Graph-Based Recommender Systems (Extended abstract). ICDE (TKDE Poster Track), 2023.

  47. Yuxin Ying, Fuzhen Zhuang*, Yongchun Zhu, Deqing Wang, Hongwei Zheng.: CAMUS: Attribute-Aware Counterfactual Augmentation for Minority Users in Recommendation. TheWebConf 2023.

  48. Yuanzhou Yao, Zhao Zhang, Kaijia Yang, Huasheng Liang, Qiang Yan, Fuzhen Zhuang, Boyu Diao, Yongjun Xu, Chao Li.: A Knowledge Enhanced Hierarchical Fusion Network for CTR Prediction under Account Search Senario in WeChat. TheWebConf 2023 (Industry Track).

  49. Ningjing Wang, Deqing Wang, Ting Jiang, Chenguang Du, Chuyu Fang, Fuzhen Zhuang.: Hierarchical Neural Topic Model with embedding cluster and neural variational inference. SDM 2023.

    50. 2022

  50. Ting Jiang, Jian Jiao, Shaohan Huang, Zihan Zhang, deqing wang, Fuzhen Zhuang, Furu Wei, Haizhen Huang, Denvy Deng, Qi Zhang.: PromptBERT: Improving BERT Sentence Embeddings with Prompts. EMNLP 2022.

  51. Ting Jiang, Deqing Wang, Leilei Sun, Zhongzhi Chen, Fuzhen Zhuang, Qinghong Yang.: Exploiting Global and Local Hierarchies for Hierarchical Text Classification. EMNLP 2022.

  52. Wei Chen, Jinglong Du, Zhao Zhang, Fuzhen Zhuang*, Zhongshi He.: A Hierarchical Interactive Network for Joint Span-based Aspect-Sentiment Analysis. COLING 2022.

  53. Fuwei Zhang, Zhao Zhang, Xiang Ao, Fuzhen Zhuang, Yongjun Xu, Qing He.: Along the Time: Timeline-traced Embedding for Temporal Knowledge Graph Completion. CIKM 2022.

  54. Hao Geng, Deqing Wang, Fuzhen Zhuang, Xuehua Ming, Chenguang Du, Ting Jiang, Haolong Guo, Rui Liu.: Modeling Dynamic Heterogeneous Graph and Node Importance for Future Citation Prediction. CIKM 2022.

  55. Shuokai Li, Yongchun Zhu, Ruobing Xie, Zhenwei Tang, Zhao Zhang, Fuzhen Zhuang, Qing He, Hui Xiong.: Customized Conversational Recommender Systems. ECML/PKDD 2022.

  56. Xiexiong Lin, Huaisong Li, Tao Huang, Feng Wang, Taifeng Wang, Tianyi Zhang, Fuzhen Zhuang, Linlin Chao.: A Logic Aware Neural Generation Method for Explainable Data-to-text. KDD 2022.

  57. Zhenwei Tang, Shichao Pei, Zhao Zhang, Yongchun Zhu, Fuzhen Zhuang, Robert Hoehndorf, Xiangliang Zhang.: Positive-Unlabeled Learning with Adversarial Data Augmentation for Knowledge Graph Completion. IJCAI 2022.

  58. Shuokai Li, Ruobing Xie, Yongchun Zhu, Xiang Ao, Fuzhen Zhuang, Qing He.: User-Centric Conversational Recommendation with Multi-Aspect User Modeling. SIGIR 2022. (Long)

  59. Yongchun Zhu, Qiang Sheng, Juan Cao, Shuokai Li, Danding Wang, Fuzhen Zhuang.: Generalizing to the Future: Mitigating Entity Bias in Fake News Detection. SIGIR 2022. (Short)

  60. Yiqing Wu, Ruobing Xie, Yongchun Zhu, Fuzhen Zhuang, Xiang Ao, Xu Zhang, Leyu Lin, Qing He.: Selective Fairness in Recommendation via Prompts. SIGIR 2022. (Short)

  61. Yiqing Wu, Ruobing Xie, Yongchun Zhu, Xiang Ao, Xin Chen, Xu Zhang, Fuzhen Zhuang, Leyu Lin, Qing He.: Multi-view Multi-behavior Contrastive Learning in Recommendation. DASFAA 2022.

  62. Yiqi Tong, Fuzhen Zhuang*, Deqing Wang, Haochao Ying, Binling Wang.: Improving Biomedical Named Entity Recognition with A Unified Multi-task MRC Framework. ICASSP 2022.

  63. Zhendong Chen, Siu Cheung Hui, Lejian Liao, Fuzhen Zhuang, Fei Li, Meihuizi Jia, Jiaqi Li.: EvidenceNet: Evidence Fusion Network for Fact Verification. TheWebConf 2022.

  64. Fuwei Zhang, Zhao Zhang, Xiang Ao, Dehong Gao, Fuzhen Zhuang, Yi Wei, Qing He.: Mind the Gap: Cross-Lingual Information Retrieval with Hierarchical Knowledge Enhancement. AAAI 2022.

  65. Yongchun Zhu, Zhenwei Tang, Yudan Liu, Fuzhen Zhuang*, Ruobing Xie, Xu Zhang, Leyu Lin, Qing He.: Personalized Transfer of User Preferences for Cross-domain Recommendation. WSDM 2022.

    66. 2021

  66. Ying Sun, Hengshu Zhu*, Chuan Qin, Fuzhen Zhuang*, Qing He, Hui Xiong.: Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation. NeurIPS 2021.

  67. Tianxin Wang, Fuzhen Zhuang*, Zhiqiang Zhang, Daixin Wang, Jun Zhou and Qing He.: Low-dimensional Alignment for Cross-Domain Recommendation. CIKM 2021.

  68. Runchuan Wang, Zhao Zhang, Fuzhen Zhuang*, Dehong Gao, Yi Wei and Qing He.: Adversarial Domain Adaptation for Cross-lingual Information Retrieval with Multilingual BERT. CIKM 2021.

  69. Yuanxin Zhuang, Chuan Shi, Cheng Yang, Fuzhen Zhuang, Yangqiu Song.: Semantic-Specific Hierarchical Alignment Network for Heterogeneous Graph Adaptation. ECML 2021.

  70. Yongchun Zhu,Yudan Liu, Ruobing Xie, Fuzhen Zhuang*, Xiaobo Hao, Kaikai Ge, Xu Zhang, Leyu Lin, Juan Cao.: Learn to Expand Audience via Meta Hybrid Experts and Critics. KDD 2021.

  71. Denghui Zhang, Zixuan Yuan, Yanchi Liu, Hao Liu, Zuohui Fu, Fuzhen Zhuang, Hui Xiong, Haifeng Chen.: Domain-oriented Language Modeling with Adaptive Hybrid Masking and Optimal Transport Alignment. KDD 2021.

  72. Dongbo Xi, Zhen Chen, Peng Yan, Yinger Zhang, Yongchun Zhu, Fuzhen Zhuang, Yu Chen.: Modeling the Sequential Dependence among Audience Multi-step Conversions with Multi-task Learning for Customer Acquisition. KDD 2021.

  73. Qi Zhang, Hengshu Zhu, Ying Sun, Hao Liu, Fuzhen Zhuang, Hui Xiong.: Talent Demand Forecasting with Attentive Neural Sequential Model. KDD 2021.

  74. Yu Zhao, Han Zhou, Ruobing Xie, Fuzhen Zhuang, Qing Li, Ji Liu.: Incorporating Global Information in Local Attention for Knowledge Representation Learning. Findings of ACL 2021.

  75. Hao Chen, Fuzhen Zhuang*, Li Xiao, Ling Ma, Haiyan Liu, Ruifang Zhang, Huiqin Jiang, Qing He.: AMA-GCN: Adaptive Multi-layer Aggregation Graph Convolutional Network for Disease Prediction. IJCAI 2021.

  76. Yongchun Zhu, Ruobing Xie, Fuzhen Zhuang*, Kaikai Ge, Ying Sun, Xu Zhang, Leyu Lin and Juan Cao.: Learning to Warm Up Cold Item Embeddings for Cold-start Recommendation with Meta Scaling and Shifting Networks. SIGIR 2021.

  77. Yongchun Zhu, Kaikai Ge, Fuzhen Zhuang*, Ruobing Xie, Dongbo Xi, Xu Zhang, Leyu Lin, Qing He.: Transfer-Meta Framework for Cross-domain Recommendation to Cold-Start Users. SIGIR 2021.

  78. Ying Sun, Fuzhen Zhuang*, Hengshu Zhu, Qing He and Hui Xiong.: Cost-Effective and Interpretable Job Skill Recommendation with Deep Reinforcement Learning. TheWebConf 2021.

  79. Binghao Liu, Pengpeng Zhao, Fuzhen Zhuang, Xuefeng Xian, Yanchi Liu, Victor S. Sheng.: Knowledge-aware Hypergraph Neural Network for Recommender Systems. DASFAA 2021.

  80. Chengheng Li, Yongjing Hao, Pengpeng Zhao, Fuzhen Zhuang, Yanchi Liu, Victor S. Sheng.: Tell me Where to Go Next: Improving POI Recommendation via Conversation. DASFAA 2021.

  81. Dongbo Xi, Bowen Song, Fuzhen Zhuang*, Yongchun Zhu, Shuai Chen, Tianyi Zhang, Yuan Qi, Qing He: Modeling the Field Value Variations and Field Interactions Simultaneously for Fraud Detection. AAAI 2021.

  82. Ting Jiang, deqing wang, Leilei Sun, Huayi Yang, Zhengyang Zhao, Fuzhen Zhuang: LightXML: Transformer with dynamic negative sampling for High-Performance Extreme Multi-label Text Classification. AAAI 2021.

  83. Qiang Zhou, Jingjing Gu, Xinjiang Lu, Fuzhen Zhuang, Yanchao Zhao, Qiuhong Wang, Xiao Zhang: Modeling Heterogeneous Relations across Multiple Modes for Potential Crowd Flow Prediction. AAAI 2021.

  84. Hao Liu, Qiyu Wu, Fuzhen Zhuang, Xinjiang Lu, Dejing Dou, Hui Xiong: Community-Aware Multi-Task Transportation Demand Prediction. AAAI 2021.

    85. 2020

  85. Jia He, Feiyang Pan, Fuzhen Zhuang*, Hui Xiong, Qing He: CCA-Flow: Deep Multi-view Subspace Learning with Inverse Autoregressive Flow. ACML 2020.

  86. Yiqing Wu, Ying Sun, Fuzhen Zhuang*, Deqing Wang, xiangliang Zhang, Qing He: Mate-path Hierarchical Heterogeneous Graph Convolution Network for High Potential Scholar Recognition. ICDM 2020.

  87. Tianzhu Chen, Fenghua Li, Fuzhen Zhuang, Liang Fang, and Yunchuan Guo: The Linear Geometry Structure of Label Matrix for Multi-label Learning. DEXA 2020.

  88. Jingbo Zhou, Zhenwei Tang, Min Zhao, Xiang Ge, Fuzhen Zhuang, Meng Zhou, Liming Zou, Chenglei Yang and Hui Xiong: Intelligent Exploration for User Interface Modules of Mobile App with Collective Learning. KDD 2020.

  89. Dongbo Xi, Fuzhen Zhuang*, Bowen Song, Yongchun Zhu, Shuai Chen, Dan Hong, Tao Chen, Xi Gu and Qing He: Neural Hierarchical Factorization Machines for User's Event Sequence Analysis. SIGIR 2020.

  90. Anjing Luo, Pengpeng Zhao, Yanchi Liu, Fuzhen Zhuang, Deqing Wang, Jiajie Xu, Junhua Fang and Victor Sheng: Collaborative Self-Attention Network for Session-based Recommendation. IJCAI 2020: 2591-2597.

  91. Haoran Yan, Pengpeng Zhao, Fuzhen Zhuang, Deqing Wang, Yanchi Liu and Victor Sheng: Cross-Domain Recommendation with Adversarial Examples. DASFAA 2020.

  92. Yanghong Wu, Pengpeng Zhao, Yanchi Liu, Victor Sheng, Junhua Fang and Fuzhen Zhuang: Vector-Level and Bit-Level Feature Adjusted Factorization Machine for Sparse Prediction. DASFAA 2020.

  93. Tianxin Wang, Jingwu Chen, Fuzhen Zhuang*, Leyu Lin, Feng Xia, Lihuan Du and Qing He: Capturing Attraction Distribution: Sequential Attentive Network for Dwell Time Prediction. ECAI 2020.

  94. Yongchun Zhu, Dongbo Xi, Bowen Song, Fuzhen Zhuang*, Shuai Chen, Xi Gu and Qing He: Modeling Users' Behavior Sequences with Hierarchical Explainable Network for Cross-domain Fraud Detection. WWW 2020: 928-938.

  95. Dongbo Xi, Fuzhen Zhuang*, Ganbin Zhou, Xiaohu Cheng, Fen Lin and Qing He: Domain Adaptation with Category Attention Network for Deep Sentiment Analysis. WWW 2020: 3133-3139.

  96. Jian Liu, Pengpeng Zhao, Fuzhen Zhuang, Yanchi Liu, Victor S. Sheng, Jiajie Xu, Xiaofang Zhou and Hui Xiong: Exploiting Aesthetic Preference in Deep Cross Networks for Cross-domain Recommendation. WWW 2020: 2768-2774.

  97. Zhao Zhang, Fuzhen Zhuang*, Hengshu Zhu, Zhiping Shi, Hui Xiong, Qing He: Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion. AAAI 2020: 9612-9619.

    98. 2019

  98. Yuyang Ye, Hengshu Zhu, Tong Xu, Fuzhen Zhuang, Runlong Yu, Hui Xiong: Identifying High Potential Talent: A Neural Network Based Dynamic Social Profiling Approach. ICDM 2019: 718-727.

  99. Cheng Liu, Jingjing Gu, Zujia Yan, Fuzhen Zhuang, Yunyun Wang: SDC-causing Error Detection Based on Lightweight Vulnerability Prediction. ACML 2019: 1049-1064.

  100. Xiao Zhang, Fuzhen Zhuang, Wenzhong Li, Haochao Ying, Hui Xiong, Sanglu Lu: Inferring Mood Instability via Smartphone Sensing: A Multi-View Learning Approach. ACM Multimedia 2019: 1401-1409.

  101. Ying Sun, Fuzhen Zhuang*, Hengshu Zhu, Xin Song, Qing He, Hui Xiong: The Impact of Person-Organization Fit on Talent Management: A Structure-Aware Convolutional Neural Network Approach. KDD 2019: 1625-1633.

  102. Jiejie Zhao, Bowen Du, Leilei Sun, Fuzhen Zhuang, Weifeng Lv, Hui Xiong: Multiple Relational Attention Network for Multi-task Learning. KDD 2019: 1123-1131.

  103. Chuan Qin, Hengshu Zhu, Chen Zhu, Tong Xu, Fuzhen Zhuang, Chao Ma, Jingshuai Zhang, Hui Xiong: DuerQuiz: A Personalized Question Recommender System for Intelligent Job Interview. KDD 2019: 2165-2173.

  104. Fei Yi, Zhiwen Yu, Fuzhen Zhuang, Bin Guo: Neural Network based Continuous Conditional Random Field for Fine-grained Crime Prediction. IJCAI 2019: 4157-4163.

  105. Chengfeng Xu, Pengpeng Zhao, Yanchi Liu, Victor S. Sheng, Jiajie Xu, Fuzhen Zhuang, Junhua Fang, Xiaofang Zhou: Graph Contextualized Self-Attention Network for Session-based Recommendation. IJCAI2019: 3940-3946.

  106. Yongchun Zhu, Fuzhen Zhuang*, Deqing Wang: Aligning Domain-Specific Distribution and Classifier for Cross-Domain Classification from Multiple Sources. AAAI 2019: 5989-5996.

  107. Dongbo Xi, Fuzhen Zhuang*, Yanchi Liu, Jingjing Gu, Hui Xiong, Qing He: Modelling of Bi-Directional Spatio-Temporal Dependence and Users' Dynamic Preferences for Missing POI Check-In Identification. AAAI 2019: 5458-5465.

  108. Pengpeng Zhao, Haifeng Zhu, Yanchi Liu, Jiajie Xu, Zhixu Li, Fuzhen Zhuang, Victor S. Sheng, Xiaofang Zhou: Where to Go Next: A Spatio-Temporal Gated Network for Next POI Recommendation. AAAI2019: 5877-5884.

  109. Feiyang Pan, Qingpeng Cai, Pingzhong Tang, Fuzhen Zhuang, Qing He: Policy Gradients for Contextual Recommendations. WWW 2019: 1421-1431.

  110. Yongchun Zhu, Fuzhen Zhuang*, Jingyuan Yang, Xi Yang, Qing He: Adaptively Transfer Category-Classifier for Handwritten Chinese Character Recognition. PAKDD (1) 2019: 110-122.

  111. Yugang Ji, Chuan Shi, Fuzhen Zhuang, Philip S. Yu: Integrating Topic Model and Heterogeneous Information Network for Aspect Mining with Rating Bias. PAKDD (1) 2019: 160-171.

    112. 2018

  112. Jia He , Rui Liu , Fuzhen Zhuang* , Fen Lin , Cheng Niu , Qing He : A General Cross-Domain Recommendation Framework via Bayesian Neural Network. ICDM 2018 : 1001-1006.

  113. Baoyu Jing , Chenwei Lu , Deqing Wang , Fuzhen Zhuang , Cheng Niu : Cross-Domain Labeled LDA for Cross-Domain Text Classification. ICDM 2018 : 187-196.

  114. Yuanbo Xu , Yongjian Yang , Jiayu Han , En Wang , Fuzhen Zhuang , Hui Xiong : Exploiting the Sentimental Bias between Ratings and Reviews for Enhancing Recommendation. ICDM 2018 : 1356-1361.

  115. Fei Yi , Zhiwen Yu , Fuzhen Zhuang , Xiao Zhang , Hui Xiong : An Integrated Model for Crime Prediction Using Temporal and Spatial Factors. ICDM 2018 : 1386-1391.

  116. Zhao Zhang , Fuzhen Zhuang* , Meng Qu , Fen Lin , Qing He : Knowledge Graph Embedding with Hierarchical Relation Structure. EMNLP 2018 : 3198-3207.

  117. Zhao Zhang , Fuzhen Zhuang , Zheng-Yu Niu , Deqing Wang , Qing He : MultiE: Multi-Task Embedding for Knowledge Base Completion. CIKM 2018 : 1715-1718.

  118. Ying Sun , Hengshu Zhu , Fuzhen Zhuang* , Jingjing Gu , Qing He : Exploring the Urban Region-of-Interest through the Analysis of Online Map Search Queries. KDD 2018 : 2269-2278.

  119. Haochao Ying , Fuzhen Zhuang , Fuzheng Zhang , Yanchi Liu , Guandong Xu , Xing Xie , Hui Xiong , Jian Wu : Sequential Recommender System based on Hierarchical Attention Networks. IJCAI 2018 : 3926-3932.

  120. Xiao Zhang , Wenzhong Li , Vu Nguyen , Fuzhen Zhuang* , Hui Xiong , Sanglu Lu : Label-Sensitive Task Grouping by Bayesian Nonparametric Approach for Multi-Task Multi-Label Learning. IJCAI 2018 : 3125-3131.

  121. Jingwu Chen , Fuzhen Zhuang , Xin Hong , Xiang Ao , Xing Xie , Qing He : Attention-driven Factor Model for Explainable Personalized Recommendation. SIGIR 2018 : 909-912.

  122. Xi Yang , Yuwei Huang , Fuzhen Zhuang* , Lishan Zhang , Shengquan Yu : Automatic Chinese Short Answer Grading with Deep Autoencoder. AIED (2) 2018 : 399-404.

  123. Yuwei Huang , Xi Yang , Fuzhen Zhuang* , Lishan Zhang , Shengquan Yu : Automatic Chinese Reading Comprehension Grading by LSTM with Knowledge Adaptation. PAKDD (1) 2018 : 118-129.

    124. 2017

  124. Jing Zheng , Fuzhen Zhuang* , Chuan Shi : Local Ensemble across Multiple Sources for Collaborative Filtering. CIKM 2017 : 2431-2434. (Accept) PDF

  125. Jia He , Changying Du , Changde Du , Fuzhen Zhuang , Qing He , Guoping Long : Nonlinear Maximum Margin Multi-View Learning with Adaptive Kernel. IJCAI 2017 : 1830-1836.PDF

  126. Fuzhen Zhuang , Lang Huang , Jia He , Jixin Ma , Qing He : Transfer Learning with Manifold Regularized Convolutional Neural Network. KSEM 2017 : 483-494. PDF

  127. Fuzhen Zhuang , Yingmin Zhou , Fuzheng Zhang , Xiang Ao , Xing Xie , Qing He : Sequential Transfer Learning: Cross-domain Novelty Seeking Trait Mining for Recommendation. WWW (Companion Volume) 2017 : 881-882. PDF

  128. Xiang Ao , Ping Luo , Jin Wang , Fuzhen Zhuang, Qing He : Mining Precise-Positioning Episode Rules from Event Sequences. ICDE 2017 : 83-86. PDF

  129. Fuzhen Zhuang , Dan Luo , Nicholas Jing Yuan , Xing Xie , Qing He : Representation Learning with Pair-wise Constraints for Collaborative Ranking. WSDM 2017 : 567-575. PDF

    130. 2016

  130. Jia He , Changying Du , Fuzhen Zhuang , Xin Yin , Qing He , Guoping Long : Online Bayesian Max-Margin Subspace Multi-View Learning. IJCAI 2016 : 1555-1561.PDF

  131. Chuan Shi , Bowei He , Menghao Zhang , Fuzhen Zhuang , Philip S. Yu , Naiwang Guo : Expenditure aware rating prediction for recommendation. BigData 2016 : 1018-1025.PDF

  132. Fuzhen Zhuang , Ping Luo , Sinno Jialin Pan , Hui Xiong , Qing He : Ensemble of Anchor Adapters for Transfer Learning. CIKM 2016 : 2335-2340. PDF

  133. Changying Du , Fuzhen Zhuang , Jia He , Qing He , Guoping Long : Learning Beyond Predefined Label Space via Bayesian Nonparametric Topic Modelling. ECML/PKDD (1) 2016 : 148-164. PDF

  134. Yitong Li , Chuan Shi , Huidong Zhao , Fuzhen Zhuang , Bin Wu : Aspect Mining with Rating Bias. ECML/PKDD (2) 2016 : 458-474. PDF

  135. Jing Zheng , Jian Liu , Chuan Shi , Fuzhen Zhuang , Jingzhi Li , Bin Wu : Dual Similarity Regularization for Recommendation. PAKDD (2) 2016 : 542-554. PDF

  136. Huifang Ma , Meihuizi Jia , Xianghong Lin , Fuzhen Zhuang : Tag correlation and user social relation based microblog recommendation. IJCNN 2016 : 2424-2430. PDF

    137. 2015

  137. Fuzhen Zhuang , Dan Luo , Xin Jin , Hui Xiong , Ping Luo , Qing He : Representation Learning via Semi-Supervised Autoencoder for Multi-task Learning. ICDM 2015 : 1141-1146.PDF

  138. Xin Jin , Fuzhen Zhuang , Sinno Jialin Pan , Changying Du , Ping Luo , Qing He : Heterogeneous Multi-task Semantic Feature Learning for Classification. CIKM 2015 : 1847-1850. PDF

  139. Xin Jin , Ping Luo , Fuzhen Zhuang , Jia He , Qing He : Collaborating between Local and Global Learning for Distributed Online Multiple Tasks. CIKM 2015 : 113-122.PDF

  140. Fuzhen Zhuang , Xiaohu Cheng , Ping Luo , Sinno Jialin Pan , Qing He : Supervised Representation Learning: Transfer Learning with Deep Autoencoders. IJCAI 2015 : 4119-4125. PDF

  141. Changying Du , Shandian Zhe , Fuzhen Zhuang , Yuan Qi , Qing He , Zhongzhi Shi : Bayesian Maximum Margin Principal Component Analysis. AAAI 2015 : 2582-2588. PDF

  142. Xiang Ao , Ping Luo , Chengkai Li , Fuzhen Zhuang , Qing He : Online Frequent Episode Mining. ICDE 2015 : 891-902. PDF

  143. Xinyu Wu , Ping Luo , Qing He , Tianshu Feng , Fuzhen Zhuang : Festival, Date and Limit Line: Predicting Vehicle Accident Rate in Beijing. SDM 2015 : 945-953. PDF

    144. 2014

  144. Fuzhen Zhuang, Xiaohu Cheng, Sinno Jialin Pan, Wenchao Yu, Qing He, Zhongzhi Shi: Transfer Learning with Multiple Sources via Consensus Regularized Autoencoders. ECML/PKDD (3) 2014: 417-431. PDF

  145. Xin Jin, Fuzhen Zhuang, Hui Xiong, Changying Du, Ping Luo, Qing He: Multi-task Multi-view Learning for Heterogeneous Tasks. CIKM 2014: 441-450. PDF

  146. Wenjuan Luo, Fuzhen Zhuang, Xiaohu Cheng, Qing He, Zhongzhi Shi: Ratable Aspects over Sentiments: Predicting Ratings for Unrated Reviews. ICDM 2014. PDF

  147. Changying Du, Jia He, Fuzhen Zhuang, Yuan Qi, Qing He: Nonparametric Bayesian Multi-Task Large-margin Classification. ECAI 2014: 255-260. PDF

  148. Xiang Ao, Ping Luo, Chengkai Li, Fuzhen Zhuang, Qing He, Zhongzhi Shi: Discovering and learning sensational episodes of news events. WWW (Companion Volume) 2014 : 217-218. PDF

  149. Shuo Han, Fuzhen Zhuang, Qing He, Zhongzhi Shi: Balanced Seed Selection for Budgeted Influence Maximization in Social Networks. PAKDD (1) 2014 : 65-77. PDF

    150. 2013

  150. Fuzhen Zhuang, Ping Luo, Peifeng Yin, Qing He, Zhongzhi Shi: Concept Learning for Cross-domain Text Classification: a General Probabilistic Framework. IJCAI, Beijing, China, pp.1960–1966, 2013. PDF

  151. Fuzhen Zhuang, Ping Luo, Changying Du, Qing He, Zhongzhi Shi. Triplex transfer learning: exploiting both shared and distinct concepts for text classification. ACM WSDM, Rome, Italy, pp.425–434, 2013. PDF

  152. Xin Jin, Fuzhen Zhuang, Shuihui Wang, Qing He, Zhongzhi Shi. Shared Structure Learning for Multiple Tasks with Multiple Views. ECML/PKDD 2013. PDF

  153. Wenchao Yu, Ping Luo, Guangxiang Zeng, Fuzhen Zhuang, Qing He, Zhongzhi Shi. Embedding with Autoencoder Regularization. ECML/PKDD 2013. PDF

  154. Tianfeng Shang, Qing He, Fuzhen Zhuang, Zhongzhi Shi. Extreme Learning Machine Combining Matrix Factorization for Collaborative Filtering. International Joint Conference on Neural Networks (IJCNN), 2013. PDF

  155. Tianfeng Shang, Qing He, Fuzhen Zhuang, Zhongzhi Shi. A New Similarity Measure Based on Preference Sequences for Collaborative Filtering. The 15th Asia-Pacific Web Conference (APWeb), Sydney, Australia, pp.384-391, 2013. PDF

    156. 2012

  156. Changying Du, Fuzhen Zhuang, Qing He, Zhongzhi Shi. Multi-task Semi-supervised Semantic Fea- ture Learning for Classification. in Proceedings of the 10th IEEE ICDM, Brussels, Belgium, pp.191-200, 2012. PDF

  157. Wenjuan Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi. Quad-tuple PLSA: Incorporating Entity and Its Rating for Aspect Identification. PAKDD, Kuala Lumpur, Malaysia, pp.292-404, 2012. PDF

    158. 2011 and Before

  158. Xudong Ma, Ping Luo, Fuzhen Zhuang, Qing He, Zhongzhi Shi, Zhiyong Shen. “Combining Su- pervised and Unsupervised Models via Unconstrained Probabilistic Embedding”. in Proceedings of IJCAI, Barcelona, Spain, pp.1396-1401, 2011. PDF

  159. Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi. “D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-Defined Classification”. in Proceedings of the 10th IEEE ICDM , Sydney, Australia, pp. 709–718, 2010. PDF

  160. Fuzhen Zhuang, Ping Luo, Zhiyong Shen, Qing He, Yuhong Xiong, Zhongzhi Shi, Hui Xiong. “Collaborative Dual-PLSA: Mining Distinction and Commonality across Multiple Domains for Text Classification”. in Proceedings of the ACM 19th CIKM, Toronto, Canada, pp. 359–368, 2010. (among the 8 best paper candidates) PDF

  161. Fuzhen Zhuang, Ping Luo, Hui Xiong, Qing He, Yuhong Xiong, Zhongzhi Shi. “Exploiting Asso- ciations between Word Clusters and Document Classes for Cross-domain Text Categorization”. in Proceedings of the SIAM SDM , Columbus, Ohio, USA, pp. 13-24, 2010. (among the 12 best paper candidates) PDF

  162. Ping Luo, Fuzhen Zhuang, Hui Xiong, Yuhong Xiong, Qing He. “Transfer Learning From Multiple Source Domains via Consensus Regularization”. in Proceedings of the ACM 17th CIKM, Napa Valley, California, USA, pp. 103–112, 2008. PDF

Ph.D. Thesis

Research on Text Classification Algorithms in Transfer Learning