Meng Hua, Yuan Cheng, Hengshu Zhu*, The Career Interests of Large Language Models, Technical Report, arXiv:2407.08564, 2024
Yufei Ji, Lan Chen, Lu Wang, Jingya Hou, Xi Chen, Hengshu Zhu*, Generative AI’s labor-replacing impacts on occupations also foster short-run job opportunities for early adopters, Technical Report, SSRN:4862800, 2024
Lan Chen, Yufei Ji, Xichen Yao Hengshu Zhu*, Occupation Life Cycle, Technical Report, arXiv:2406.15373, 2024
Tianhui Ma, Yuan Cheng, Hengshu Zhu, Hui Xiong, Large Language Models are Not Stable Recommender Systems, Technical Report, arXiv:2312.15746, 2023
Chuan Qin, Le Zhang, Rui Zha, Dazhong Shen, Qi Zhang, Ying Sun, Chen Zhu, Hengshu Zhu*, Hui Xiong*, A Comprehensive Survey of Artificial Intelligence Techniques for Talent Analytics, Technical Report, arXiv:2307.03195, 2023
Lan Chen, Xi Chen, Shiyu Wu, Yaqi Yang, Chang Meng, Hengshu Zhu*, The Future of ChatGPT-enabled Labor Market: A Preliminary Study in China, Technical Report, arXiv:2304.09823, 2023
Zhi Zheng, Zhaopeng Qiu, Xiao Hu, Likang Wu, Hengshu Zhu*, Hui Xiong, Generative Job Recommendations with Large Language Model, Technical Report, arXiv:2307.02157, 2023
Ying Sun, Hengshu Zhu*, Lu Wang, Le Zhang, Hui Xiong*, Large-scale online job search behaviors reveal labor market shifts amid COVID-19, In Nature Cities, 2024
Likang Wu, Zhi Zheng, Zhaopeng Qiu, Hao Wang*, Hongchao Gu, Tingjia Shen, Chuan Qin, Chen Zhu, Hengshu Zhu*, Qi Liu, Hui Xiong*, Enhong Chen*, A Survey on Large Language Models for Recommendation, In World Wide Web (WWWJ), 2024 [arXiv:2305.19860]
Dazhong Shen, Chuan Qin, Qi Zhang, Hengshu Zhu*, Hui Xiong, Handling Over-Smoothing and Over-Squashing in Graph Convolution with Maximization Operation, In IEEE Transactions on Neural Networks and Learning Systems (IEEE TNNLS), 2024
Kaichun Yao, Hao Wang, Chuan Qin, Hengshu Zhu, Yanjun Wu, Libo Zhang, CARL: Unsupervised Code-Based Adversarial Attacks for Programming Language Models via Reinforcement Learning, In ACM Transactions on Software Engineering and Methodology (ACM TOSEM), 2024
Huishi Luo, Fuzhen Zhuang, Ruobing Xie, Hengshu Zhu, Deqing Wang, Zhulin An, Yongjun Xu, A survey on causal inference for recommendation, In The Innovation, 2024
Rui Zha, Ying Sun, Chuan Qin, Le Zhang, Tong Xu*, Hengshu Zhu*, Enhong Chen, Towards Unified Representation Learning for Career Mobility Analysis with Trajectory Hypergraph, In ACM Transactions on Information Systems (ACM TOIS), 2024
Yuyang Ye, Hengshu Zhu*, Tianyi Cui, Runlong Yu, Le Zhang, Hui Xiong*, University Evaluation through Graduate Employment Prediction: An Influence based Graph Autoencoder Approach, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024
Zhi Zheng, Xiao Hu, Zhaopeng Qiu, Yuan Cheng, Shanshan Gao, Yang Song, Hengshu Zhu*, Hui Xiong*, Bilateral Multi-Behavior Modeling for Reciprocal Recommendation in Online Recruitment, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024
Xiaoshan Yu, Chuan Qin, Dazhong Shen, Haiping Ma, Le Zhang, Hengshu Zhu, Xingyi Zhang, Hui Xiong, RDGT: Enhancing Group Cognitive Diagnosis with Relation-Guided Dual-Side Graph Transformer, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2024
Zhihao Guang, Jiaqi Yang, Yang Yang, Hengshu Zhu, Wenjie Li, Hui Xiong, JobFormer: Skill-Aware Job Recommendation with Semantic-Enhanced Transformer, In ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2024
Chuang Zhao, Hongke Zhao, Hengshu Zhu, Zhenya Huang, Nan Feng, Enhong Chen, Hui Xiong, Bi-discriminator Domain Adversarial Neural Networks with Class-Level Gradient Alignment, In IEEE Transactions on Systems, Man, and Cybernetics: Systems (IEEE TSMC-S), 2024
Rui Chang, Xin Wei, Xi Zhang, Hui Xiong Hengshu Zhu, How recommendation letters affect career Mobility: Evidence from a social networking sites LinkedIn, In Computers in Human Behavior, Volume 152, 2024
Dazhong Shen, Hengshu Zhu*, Keli Xiao, Xi Zhang, Hui Xiong*, Exploiting Connections among Personality, Job Position, and Work Behavior: Evidence from Joint Bayesian Learning, In ACM Transactions on Management Information Systems (ACM TMIS), 2023.
Chao Wang, Hengshu Zhu*, Chen Zhu, Chuan Qin, Enhong Chen, Hui Xiong*, SetRank: A Setwise Bayesian Approach for Collaborative Ranking in
Recommender System, In ACM Transactions on Information Systems (ACM TOIS), 2023
Chuan Qin, Hengshu Zhu*, Dazhong Shen, Ying Sun, Kaichun Yao, Peng Wang, Hui Xiong*, Automatic Skill-oriented Question Generation and Recommendation for Intelligent Job Interviews, In ACM Transactions on Information Systems (ACM TOIS), 2023
Yang Yang, Chubing Zhang, Xin Song, Zheng Dong, Hengshu Zhu*, Wenjie Li*, Contextualized Knowledge Graph Embedding for Explainable Talent Training Course Recommendation, In ACM Transactions on Information Systems (ACM TOIS), 2023
Jindong Han, Hao Liu, Hengshu Zhu, Hui Xiong, Kill Two Birds with One Stone: A Multi-View Multi-Adversarial Learning Approach for Joint Air Quality and Weather Prediction, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2023
Han Wu, Guanqi Zhu, Qi Liu, Hengshu Zhu, Hao Wang, Hongke Zhao, Chuanren Liu, Enhong Chen, Hui Xiong, A Multi-aspect Neural Tensor Factorization Framework for Patent Litigation Prediction, In IEEE Transactions on Big Data (IEEE TBD), 2023.
Rui Zha, Chuan Qin, Le Zhang, Dazhong Shen, Tong Xu, Hengshu Zhu, Enhong Chen, Career Mobility Analysis with Uncertainty-aware Graph Autoencoders: A Job Title Transition Perspective, In IEEE Transactions on Computational Social Systems (IEEE TCSS), 2023
Hongke Zhao, Chuang Zhao, Xi Zhang, Nanlin Liu, Hengshu Zhu, Qi Liu, Hui Xiong, An Ensemble Learning Approach with Gradient Resampling for Class-imbalance Problems, In INFORMS Journal on Computing (JOC), 2023
Chenguang Du, Kaichun Yao, Hengshu Zhu, Deqing Wang, Fuzhen Zhuang, Hui Xiong, Mining Technology Trends in Scientific Publications: A Graph Propagated Neural Topic Modeling Approach, In Knowledge and Information Systems (KAIS), 2023
Junji Jiang, Likang Wu, Hongke Zhao, Hengshu Zhu, Wei Zhang, Forecasting movements of stock time series based on hidden state guided deep learning approach, In Information Processing & Management (IPM), 2023
Qingxin Meng, Keli Xiao, Dazhong Shen, Hengshu Zhu*, Hui Xiong*, Fine-Grained Job Salary Benchmarking with a Nonparametric Dirichlet-process-based Latent Factor Model, In INFORMS Journal on Computing (JOC), 2022
Pengzhan Guo, Keli Xiao*, Zeyang Ye, Hengshu Zhu*, Wei Zhu*, Intelligent Career Planning via Stochastic Subsampling Reinforcement Learning, In Scientific Reports, 2022.
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, In ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2022
Hao Liu, Qingyu Guo, Hengshu Zhu*, Fuzhen Zhuang, Shengwen Yang, Dejing Dou, Hui Xiong*, Who will Win the Data Science Competition? Insights from KDD Cup 2019 and Beyond, In ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 2022
Chuan Qin, Kaichun Yao, Hengshu Zhu*, Tong Xu, Dazhong Shen, Enhong Chen, Hui Xiong*, Towards Automatic Job Description Generation with Capability-Aware Neural Networks, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022
Yuyang Ye, Zheng Dong, Hengshu Zhu*, Tong Xu, Xin Song, Runlong Yu, Hui Xiong*, MANE: Organizational Network Embedding with Multiplex Attentive Neural Networks, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022
Hongke Zhao, Yihang Cheng, Xi Zhang*, Hengshu Zhu*, Qi Liu, Hui Xiong, Wei Zhang, What is Market Talking about Market-oriented Prospect Analysis for Entrepreneur Fundraising, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2022
Yang Yang, Hongchen Wei, Hengshu Zhu, Dianhai Yu, Hui Xiong, Jian Yang, Exploiting Cross-Modal Prediction and Relation Consistency for Semi-Supervised Image Captioning, In IEEE Transactions on Cybernetics (IEEE TCYB), 2022
Xi Zhang, Xin Wei, Carol XJ Ou, Emiel Caron, Hengshu Zhu, Hui Xiong, From Human-AI Confrontation to Human-AI Symbiosis in Society 5.0: Transformation Challenges and Mechanisms, In IT Professional, 2022.
Hongting Niu, Ying Sun, Hengshu Zhu, Cong Geng, Jiuchun Yang, Hui Xiong, Bo Lang, Exploring the Tidal Effect of Urban Business District with Large-scale Human Mobility Data, In Frontiers of Computer Science (FCS), 2022
Yiqi Tong, Fuzhen Zhuang*, Huajie Zhang, Chuyu Fang, Yu Zhao, Deqing Wang, Hengshu Zhu, Bin Ni, Improving Biomedical Named Entity Recogni-tion by Dynamic Caching Inter-sentence Infor-mation, In Bioinformatics, 2022.
Dazhong Shen, Chuan Qin, Hengshu Zhu*, Tong Xu, Enhong Chen, Hui Xiong*, Joint Representation Learning with Relation-enhanced Topic Models for Intelligent Job Interview Assessment, In ACM Transactions on Information Systems (ACM TOIS), 2021
Chao Wang, Hengshu Zhu*, Peng Wang, Chen Zhu, Xi Zhang, Enhong Chen, Hui Xiong*, Personalized and Explainable Employee Training Course Recommendations: A Bayesian Variational Approach, In ACM Transactions on Information Systems (ACM TOIS), 2021
Qi Zhang, Hengshu Zhu*, Qi Liu, Enhong Chen, Hui Xiong*, Exploiting Real-time Search Engine Queries for Earthquake Detection: A Summary of Result, In ACM Transactions on Information Systems (ACM TOIS), 2021
Ying Sun, Fuzhen Zhuang*, Hengshu Zhu*, Qing He, Hui Xiong, Modeling the Impact of Person-Organization Fit on Talent Management with Structure-Aware Attentive Neural Networks, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021
Zhao Zhang, Fuzhen Zhuang, Hengshu Zhu, Chao Li, Hui Xiong, Qing He, Yongjun Xu, Towards Robust Knowledge Graph Embedding via Multi-task Reinforcement Learning, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021
Yang Yang, Jia-Qi Yang, Ran Bao, De-Chuan Zhan, Hengshu Zhu, Xiao-Ru Gao, Hui Xiong, Jian Yang, Corporate Relative Valuation using Heterogeneous Multi-Modal Graph Neural Network, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021
Yang Yang, Zhen-Qiang Sun, Hengshu Zhu, Yanjie Fu, Yuanchun Zhou, Hui Xiong, Jian Yang, Learning Adaptive Embedding Considering Incremental Class, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2021
Mingfei Teng, Hengshu Zhu*, Chuanren Liu, Hui Xiong*, Exploiting Networks Fusion for Organizational Turnover Prediction, In ACM Transactions on Management Information Systems (ACM TMIS), 2021
Hongting Niu, Hengshu Zhu, Ying Sun, Xinjiang Lu, Jing Sun, Zhiyuan Zhao, Hui Xiong, Bo Lang, Exploring the Risky Travel Area and Behavior of Car-hailing Service, In ACM Transactions on Intelligent Systems and Technology (ACM TIST), 2021
Yi Du, Hanxue Wang, Wenjuan Cui, Hengshu Zhu, Yunchang Guo, Fayaz Ali Dharejo, Yuanchun Zhou Foodborne Disease Risk Prediction using Multi-Graph Structural LSTM: Algorithm Design and Validation Study, In JMIR Medical Informatics, 2021
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, In Scientific Reports, 2020.
[Paper]
Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He, A Comprehensive Survey on Transfer Learning, In Proceedings of the IEEE (PIEEE), 2020
[Preprint]
Qingyu Guo, Fuzhen Zhuang, Chuan Qin, Hengshu Zhu, Xing Xie, Hui Xiong, Qing He, A Survey on Knowledge Graph based Recommender Systems, In IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2020
[Preprint]
Hao Lin, Hengshu Zhu*, Junjie Wu*, Yuan Zuo, Chen Zhu, Hui Xiong, Enhancing Employer Brand Evaluation with Collaborative Topic Regression Models, In ACM Transactions on Information Systems (ACM TOIS), 2020.
Chuan Qin, Hengshu Zhu*, Tong Xu, Chen Zhu, Chao Ma, Enhong Chen, Hui Xiong*, An Enhanced Neural Network Approach to Person-Job Fit in Talent Recruitment, In ACM Transactions on Information Systems (ACM TOIS), 2020.
Renjun Hu, Jingbo Zhou, Xinjiang Lu, Hengshu Zhu, Shuai Ma, Hui Xiong, NCF: A Neural Context Fusion Approach to Raw Mobility Annotation, In IEEE Transactions on Mobile Computing (IEEE TMC), 2020.
Dongbo Xi, Fuzhen Zhuang, Yanchi Liu, Hengshu Zhu, Pengpeng Zhao, Chang Tan, and Qing He, Exploiting Bi-directional Global Transition Patterns and Personal Preferences for Missing POI Category Identification, In Neural Networks , 2020
Tong Xu, Hengshu Zhu, Hui Xiong, Hao Zhong, Enhong Chen, Exploring the Social Learning of Taxi Drivers in Latent Vehicle-to-Vehicle Network, In IEEE Transactions on Mobile Computing (IEEE TMC), 2019
Binbin Jin, Hongke Zhao, Zhenya Huang, Enhong Chen, Qi Liu, Hengshu Zhu, Shui Yu, Promotion of Answer Value Measurement with Domain Effects in Community Question Answering Systems, IEEE Transactions on Systems, Man and Cybernetics: Systems (IEEE TSMC-S), 2019.
Zikai Yin, Tong Xu, Hengshu Zhu, Chen Zhu, Enhong Chen, Hui Xiong, Matching of Social Events and Users: A Two-Way Selection Perspective, World Wide Web (WWWJ), 2019.
Chen Zhu, Hengshu Zhu*, Hui Xiong*, Chao Ma, Fang Xie, Pengliang Ding, Pan Li, Person-Job Fit: Adapting the Right Talent for the Right Job with Joint Representation Learning, In ACM Transactions on Management Information Systems (ACM TMIS), 2018.
[MIT Technology Review]
[Fast Company]
[Tech Xplore]
Tong Xu, Hengshu Zhu, Hao Zhong, Guannan Liu, Hui Xiong, Enhong Chen, Exploiting the Dynamic Mutual Influence for Predicting Social Event Participation , IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2018.
Huang Xu, Zhiwen Yu, Jingyuan Yang, Hui Xiong, Hengshu Zhu, Dynamic Talent Flow Analysis with Deep Sequence Prediction Modeling, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2018.
Yanjie Fu, Guannan Liu, Pengyang Wang, Yong Ge, Hui Xiong, Hengshu Zhu, Representing Urban Forms: A Collective Learning Model with Heterogeneous Human Mobility Data, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 2018.
Hongke Zhao, Qi Liu, Hengshu Zhu, Yong Ge, Enhong Chen, Yan Zhu, Junping Du, A Sequential Approach to Market State Modeling and Analysis in Online P2P Lending, IEEE Transactions on Systems, Man and Cybernetics: Systems (IEEE TSMC-S), 2017.
Enhong Chen, Guangxiang Zeng, Ping Luo, Hengshu Zhu, Jilei Tian, Hui Xiong, Discerning Individual Interests and Shared Interests for Social User Profiling, World Wide Web (WWWJ), 20(2): 417-435, March 2017.
祝恒书, 面向移动商务的数据挖掘方法及应用研究, 《中国人工智能学会通讯》 , 2016
Chen Zhu, Hengshu Zhu, Yong Ge, Enhong Chen, Qi Liu, Tong Xu, Hui Xiong, Tracking the Evolution of Social Emotions with Topic Models, Knowledge and Information System Journal (KAIS), 47(3): 517-544, 2016.
Hengshu Zhu, Hui Xiong, Yong Ge, and Enhong Chen, Discovery of Ranking Fraud for Mobile Apps, IEEE Transactions on Knowledge and Data Engineering (IEEE TKDE), 27(1):74-87, 2015.
[PDF]
[Data Set]
Hengshu Zhu, Chuanren Liu, Yong Ge, Hui Xiong, Enhong Chen, Popularity Modeling for Mobile Apps: A Sequential Approach, IEEE Transactions on Cybernetics (IEEE TCYB), 45(7): 1303-1314, 2015.
[PDF]
[Data Set]
Liyang Tang, Zhiwei Ni, Hui Xiong, Hengshu Zhu, Locating Targets Through Mention in Twitter, World Wide Web (WWWJ), 18(4): 1019-1049, 2015
Hengshu Zhu, Enhong Chen, Hui Xiong, Huanhuan Cao, Jilei Tian, Mobile App Classification with Enriched Contextual Information, IEEE Transactions on Mobile Computing (IEEE TMC) 13(7): 1550-1563, 2014.
Hengshu Zhu, Enhong Chen, Hui Xiong, Kuifei Yu, Huanhuan Cao, Jilei Tian, Mining Mobile User Preferences for Personalized Context-Aware Recommendation, ACM Transactions on Intelligent Systems and Technology (ACM TIST), 5(4):58, 2014.
[PDF]
Baoxing Huai, Enhong Chen, Hengshu Zhu, Hui Xiong, Tengfei Bao, Qi Liu, Jilei Tian, Toward Personalized Context Recognition for Mobile Users: A Semisupervised Bayesian HMM Approach, ACM Transactions on Knowledge Discovery from Data (ACM TKDD), 9(2):10, 2014.
[PDF]
Hengshu Zhu, Enhong Chen, Hui Xiong, Huanhuan Cao, Jilei Tian, Ranking User Authority with Relevant Knowledge Categories for Expert Finding, World Wide Web (WWWJ), 17:1081-1107, 2014.
Tong Xu, Hengshu Zhu, Enhong Chen, Baoxing Huai, Hui Xiong, Jilei Tian, Learning to Annotate via Social Interaction Analytics, Knowledge and Information System Journal (KAIS): 41(2): 251-276, 2014
Kuifei Yu, Hengshu Zhu, Huanhuan Cao, Baoxian Zhang, Enhong Chen, Jilei Tian, Jinghai Rao, Learning to detect subway arrivals for passengers on a train. Frontiers of Computer Science (FCS) 8(2): 316-329, 2014.
Hengshu Zhu, Enhong Chen, Huanhuan Cao, Jilei Tian, Context-Aware Expert Finding in Tag Based Knowledge Sharing Communities. International Journal of Knowledge and Systems Science (IJKSS) 3(1): 48-63, 2012.
Conference Papers:
Yihang Cheng, Xiao Hu, Chen Zhu, Hengshu Zhu*, Does More Informative Job Title Lead to More Successful Hirings? A Randomized Field Experiment on an Online Labor Market Platform, In Proceedings of the 58th Hawaii International Conference on System Sciences (HICSS-2025), 2025
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, In Proceedings of Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS-2024), 2024[Data Set] (Resource Paper)
Yaming Guo, Chen Zhu*, Hengshu Zhu*, Tieru Wu*, OT4P: Unlocking Effective Orthogonal Group Path for Permutation Relaxation, In Proceedings of Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS-2024), 2024
Hongzhan Lin, Ang Lv, Yuhan Chen, Chen Zhu, Yang Song, Hengshu Zhu, Rui Yan, Mixture of In-Context Experts Enhance LLMs' Long Context Awareness, In Proceedings of Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS-2024), 2024
Xiao Han, Chen Zhu*, Xiao Hu, Chuan Qin, Xiangyu Zhao*, Hengshu Zhu*, Adapting Job Recommendations to User Preference Drift with Behavioral-Semantic Fusion Learning, In Proceedings of the 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2024), 2024
Xiaoshan Yu, Chuan Qin*, Dazhong Shen, Shangshang Yang, Haiping Ma, Hengshu Zhu*, Xingyi Zhang*, RIGL: A Unified Reciprocal Approach for Tracing the Independent and Group Learning Processes, In Proceedings of the 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2024), 2024
Chen Yang, Sunhao Dai, Yupeng Hou, Xin Zhao, Jun Xu, Song Yang, Hengshu Zhu, Revisiting Reciprocal Recommender Systems: Metrics, Formulation, and Method, In Proceedings of the 30th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2024), 2024
Xi Chen, Chuan Qin, Zhigaoyuan Wang, Yihang Cheng, Chao Wang, Hengshu Zhu*, Hui Xiong*, Pre-DyGAE: Pre-training Enhanced Dynamic Graph Autoencoder for Occupational Skill Demand Forecasting, In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI-2024), 2024
Haiping Ma, Siyu Song, Chuan Qin, Xiaoshan Yu, Limiao Zhang, Xingyi Zhang, Hengshu Zhu, DGCD: An Adaptive Denoising GNN for Group-level Cognitive Diagnosis, In Proceedings of the 33rd International Joint Conference on Artificial Intelligence (IJCAI-2024), 2024
Zhi Zheng, Xiao Hu, Shanshan Gao, Hengshu Zhu*, Hui Xiong*, MIRROR: A Multi-View Reciprocal Recommender System for Online Recruitment, In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2024), 2024
Zhi Zheng, Wen Shuo Chao, Zhaopeng Qiu, Hengshu Zhu*, Hui Xiong*, Harnessing Large Language Models for Text-Rich Sequential Recommendation, In Proceedings of The Web Conference 2024 (WWW-2024), 2024
Liyi Chen, Chuan Qin, Ying Sun, Xin Song, Tong Xu, Hengshu Zhu, Hui Xiong, Collaboration-Aware Hybrid Learning for Knowledge Development Prediction, In Proceedings of The Web Conference 2024 (WWW-2024), 2024
Haiping Ma, Yong Yang, Chuan Qin, Xiaoshan Yu, Shangshang Yang, Xingyi Zhang, Hengshu Zhu, HD-KT: Advancing Robust Knowledge Tracing via Anomalous Learning Interaction Detection, In Proceedings of The Web Conference 2024 (WWW-2024), 2024
Likang Wu, Zhaopeng Qiu, Zhi Zheng, Hengshu Zhu*, Enhong Chen*, Exploring Large Language Model for Graph Data Understanding in Online Job Recommendations, In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-2024), 2024
Wenshuo Zhao, Zhaopeng Qiu, Likang Wu, Zhi Zheng, Hengshu Zhu*, Hao Liu*, A Cross-View Hierarchical Graph Learning Hypernetwork for Skill Demand-Supply Joint Prediction, In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-2024), 2024
Yingpeng Du, Di Luo, Rui Yan, Xiaopei Wang, Hongzhi Liu, Hengshu Zhu, Yang Song, Jie Zhang, Enhancing Job Recommendation through LLM-based Generative Adversarial Networks, In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-2024), 2024
Haiping Ma, Changqian Wang, Hengshu Zhu, Shangshang Yang, Xiaoming Zhang, Xingyi Zhang, Enhancing Cognitive Diagnosis using Un-interacted Exercises: A Collaboration-aware Mixed Sampling Approach, In Proceedings of the 38th AAAI Conference on Artificial Intelligence (AAAI-2024), 2024
Xiaoshan Yu, Chuan Qin, Qi Zhang, Chen Zhu, Haiping Ma, Xingyi Zhang, Hengshu Zhu, DISCO: A Hierarchical Disentangled Cognitive Diagnosis Framework for Interpretable Job Recommendation, In Proceedings of the 24th IEEE International Conference on Data Mining (ICDM-2024), 2024
Wenshuo Chao, Zhi Zheng, Hengshu Zhu*, Hao Liu*, Make Large Language Model a Better Ranker, In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP-2024 Findings), 2024
Feihu Jiang, Chuan Qin, Kaichun Yao, Chuyu Fang, Fuzhen Zhuang, Hengshu Zhu, Hui Xiong, Towards Efficient Resume Understanding: A Multi-Granularity Multi-Modal Pre-Training Approach, In Proceedings of IEEE Conference on Multimedia Expo 2024 (ICME-2024), 2024
Feihu Jiang, Chuan Qin, Jingshuai Zhang, Kaichun Yao, Xi Chen, Dazhong Shen, Chen Zhu Hengshu Zhu, Hui Xiong, Enhancing Question Answering for Enterprise Knowledge Bases using Large Language Models, In Proceedings of the 29th International Conference on Database Systems for Advanced Applications (DASFAA-2024), 2024
Shasha Hu, Chao Wang, Chuan Qin, Hengshu Zhu, Hui Xiong, Super-node Generation for GNN-based Recommender Systems: Enhancing Distant Node Integration via Graph Coarsening,In Proceedings of the 29th International Conference on Database Systems for Advanced Applications (DASFAA-2024), 2024
Wenxuan Zhang, Hongzhi Liu, Zhijin Dong, Yingpeng Du, Chen Zhu, Yang Song, Hengshu Zhu, Zhonghai Wu, Bridging the Information Gap Between Domain-Specific Model and General LLM for Personalized Recommendation,In Proceedings of the 8th APWeb-WAIM Joint International Conference on Web and Big Data (APWeb-WAIM 2024), 2024
Xiao Hu, Yuan Cheng, Zhi Zheng, Yue Wang, Xinxin Chi, Hengshu Zhu*, BOSS: A Bilateral Occupational-Suitability-Aware Recommender System for Online Recruitment, In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2023), 2023
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, In Proceedings of the 29th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2023), 2023
Qi Zhang, Hengshu Zhu*, Peng Wang, Enhong Chen, Hui Xiong*, Hierarchical Wi-Fi Trajectory Embedding for Indoor User Mobility Pattern Analysis, In Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp-2023), 2023
Chenguang Du, Kaichun Yao, Hengshu Zhu*, Deqing Wang, Fuzhen Zhuang, Hui Xiong, Seq-HGNN: Learning Sequential Node Representation on Heterogeneous Graph, In Proceedings of the 46th International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2023), 2023
Kaichun Yao, Jingshuai Zhang, Chuan Qin*, Xin Song, Peng Wang, Hengshu Zhu*, Hui Xiong, ResuFormer: Semantic Structure Understanding for Resumes via Multi-Modal Pre-training, In Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE-2023), 2023
Congxi Xiao, Jingbo Zhou, Jizhou Huang, Hengshu Zhu, Tong Xu, Dejing Dou, Hui Xiong, A Contextual Master-Slave Framework on Urban Region Graph for Urban Village Detection , In Proceedings of the 39th IEEE International Conference on Data Engineering (ICDE-2023), 2023
Yunfei Zhang, Chuan Qin, Dazhong Shen, Haiping Ma, Le Zhang, Xingyi Zhang, Hengshu Zhu*, ReliCD: A Reliable Cognitive Diagnosis Framework with Confidence Awareness, In Proceedings of the 23rd IEEE International Conference on Data Mining (ICDM-2023), 2023
Pengzhan Guo, Keli Xiao, Hengshu Zhu, Qingxin Meng, Preference-Constrained Career Path Optimization: An Exploration Space-Aware Stochastic Model, In Proceedings of the 23rd IEEE International Conference on Data Mining (ICDM-2023), 2023
Bowen Zheng, Yupeng Hou, Wayne Xin Zhao, Yang Song, Hengshu Zhu, Reciprocal Sequential Recommendation, In Proceedings of the 17th ACM Conference Series on Recommender Systems (RecSys-2023), 2023
Zhi Zheng, Ying Sun, Xin Song, Hengshu Zhu*, Hui Xiong*, Generative Learning Plan Recommendation for Employees: A Performance-aware Reinforcement Learning Approach, In Proceedings of the 17th ACM Conference Series on Recommender Systems (RecSys-2023), 2023
Yiwei Wang, Qingxin Meng, Alain Chong, Hengshu Zhu, Towards a Better Characterization of IT Career Development Patterns, In Proceedings of 29th Americas Conference on Information Systems (AMCIS-2023), 2023
Yang Yang, Jingshuai Zhang, Fan Gao, Xiaoru Gao, Hengshu Zhu*, DOMFN: A Divergence-Orientated Multi-Modal Fusion Network for Resume Assessment, In Proceedings of the 30th ACM International Conference on Multimedia (MM-2022) , Lisbon, Portugal, 2022.
Haiping Ma, Jingyuan Wang, Hengshu Zhu*, Xin Xia, Haifeng Zhang, Xingyi Zhang*, Lei Zhang, Reconciling Cognitive Modeling with Knowledge Forgetting: A Continuous Time-aware Neural Network Approach, In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI-2022), 2022
Wei Fan, Kunpeng Liu, Hao Liu, Hengshu Zhu, Hui Xiong, Yanjie Fu, Feature and Instance Joint Selection: A Reinforcement Learning Perspective, In Proceedings of the 31st International Joint Conference on Artificial Intelligence (IJCAI-2022), 2022
Kaichun Yao, Jingshuai Zhang, Chuan Qin, Peng Wang, Hengshu Zhu*, Hui Xiong, Knowledge Enhanced Person-Job Fit for Talent Recruitment, In Proceedings of the 38th IEEE International Conference on Data Engineering (ICDE-2022), 2022
Jinquan Hang, Zheng Dong, Hongke Zhao*, Xin Song, Peng Wang, Hengshu Zhu*, Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction, In Proceedings of The 15th International Conference on Web Search and Data Mining (WSDM-2022), 2022(Best-ranked Papers)
Zhuoning Guo, Hao Liu, Le Zhang, Qi Zhang, Hengshu Zhu, Hui Xiong, Talent Demand-Supply Joint Prediction with Dynamic Heterogeneous Graph Enhanced Meta-Learning, In Proceedings of the 28th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2022), 2022
Xin Wei, Xi Zhang, Ou, Carol, Hengshu Zhu, Identifying Turnover Contagion in Enterprise Social Networks, In Proceedings of Twenty-Eighth Americas Conference on Information Systems (AMCIS-2022), 2022
Ying Sun, Hengshu Zhu*, Chuan Qin, Fuzhen Zhuang*, Qing He, Hui Xiong, Discerning Decision-Making Process of Deep Neural Networks with Hierarchical Voting Transformation, In Proceedings of Thirty-fifth Annual Conference on Neural Information Processing Systems (NeurIPS-2021), 2021
Dazhong Shen, Chuan Qin, Chao Wang, Zheng Dong, Hengshu Zhu*, Hui Xiong*, Topic Modeling Revisited: A Document Graph-based Neural Network Perspective, In Proceedings of Thirty-fifth Annual Conference on Neural Information Processing Systems (NeurIPS-2021), 2021
Kaichun Yao, Chuan Qin, Hengshu Zhu*, Chao Ma, Jingshuai Zhang, Yi Du, Hui Xiong, An Interactive Neural Network Approach to Keyphrase Extraction in Talent Recruitment, In Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM-2021), 2021
Zheng Dong, Xin Huang*, Guorui Yuan, Hengshu Zhu*, Hui Xiong, Butterfly-Core Community Search over Labeled Graphs, In Proceedings of the 47th International Conference on Very Large Data Bases (VLDB-2021), 2021
Qi Zhang, Hengshu Zhu*, Ying Sun, Hao Liu, Fuzhen Zhuang, Hui Xiong*, Talent Demand Forecasting with Attentive Neural Sequential Model, In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2021), 2021
Le Zhang, Ding Zhou, Hengshu Zhu*, Tong Xu, Rui Zha, Enhong Chen, Hui Xiong*, Attentive Heterogeneous Graph Embedding for Job Mobility Prediction, In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2021), 2021
Weijia Zhang, Hao Liu, Lijun Zha, Hengshu Zhu, Ji Liu, Dejing Dou, Hui Xiong, MugRep: A Multi-Task Hierarchical Graph Representation Learning Framework for Real Estate Appraisal, In Proceedings of the 27th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2021), 2021
Dazhong Shen, Chuan Qin, Chao Wang, Hengshu Zhu*, Enhong Chen, Hui Xiong*, Regularizing Variational Autoencoder with Diversity and Uncertainty Awareness, In Proceedings of the 30th International Joint Conference on Artificial Intelligence (IJCAI-2021), 2021
Chao Wang, Hengshu Zhu*, Qiming Hao, Keli Xiao, Hui Xiong*, Variable Interval Time Sequence Modeling for Career Trajectory Prediction: Deep Collaborative Perspective, In Proceedings of The Web Conference 2021 (WWW-2021), 2021
Ying Sun, Fuzhen Zhuang*, Hengshu Zhu*, Qing He, Hui Xiong, Cost-Effective and Interpretable Job Skill Recommendation with Deep Reinforcement Learning, In Proceedings of The Web Conference 2021 (WWW-2021), 2021
Jindong Han, Hao Liu, Hengshu Zhu, Hui Xiong, Dejing Dou, Joint Air Quality and Weather Prediction Based on Multi-Adversarial Spatiotemporal Networks, In Proceedings of the 35th AAAI Conference on Artificial Intelligence (AAAI-2021), 2021
Yihang Cheng, Xi Zhang, Xinlin Tang, Hengshu Zhu, Is AI Better Than Human in Identifying HighPotential Talents? A Quasi-Field Experiment, In Proceedings of Twenty-Seventh Americas Conference on Information Systems (AMCIS-2021), 2021
Yuqing Zhao, Xi Zhang, Xinlin Tang, Chuan Qin, Hengshu Zhu, Embedding Fairness into the AI-based Talent Recruitment Systems: The Perspective of Environment Cycle and Knowledge Cycle, In Proceedings of Twenty-Fifth Pacific Asia Conference on Information Systems (PACIS-2021), 2021
Chao Wang, Hengshu Zhu*, Chen Zhu, Xi Zhang, Enhong Chen, Hui Xiong*, Personalized Employee Tranining Course Recommendation with Career Development Awareness, In Proceedings of The Web Conference 2020 (WWW-2020), Taipei, 2020.
Le Zhang, Tong Xu*, Hengshu Zhu*, Chuan Qin, Qingxin Meng, Hui Xiong*, Enhong Chen, Large-Scale Talent Flow Embedding for Company Competitive Analysis, In Proceedings of The Web Conference 2020 (WWW-2020), Taipei, 2020.
Chao Wang, Hengshu Zhu*, Chen Zhu, Chuan Qin, Hui Xiong*, SetRank: A Setwise Bayesian Approach for Collaborative Ranking from Implicit Feedback, In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-2020), New York City, USA, 2020
Zhao Zhang, Fuzhen Zhuang, Hengshu Zhu, Zhiping Shi, Hui Xiong, Qing He, Relational Graph Neural Network with Hierarchical Attention for Knowledge Graph Completion, In Proceedings of the 34th AAAI Conference on Artificial Intelligence (AAAI-2020), New York City, USA, 2020
Xi Zhang, Yuqing Zhao, Xinlin Tang, Hengshu Zhu, Hui Xiong, Developing Fairness Rules for Talent Intelligence Management System, In Proceedings of the 53rd Hawaii International Conference on System Sciences (HICSS-2020), Maui, Hawaii, USA, 2020
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, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2019), Anchorage, Alaska, 2019
[读芯术]
Qingxin Meng, Hengshu Zhu*, Keli Xiao, Le Zhang, Hui Xiong*, A Hierarchical Career-Path-Aware Neural Network for Job Mobility Prediction, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2019), Anchorage, Alaska, 2019
[读芯术]
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, In Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2019), Anchorage, Alaska, 2019
[读芯术]
Le Zhang, Chen Zhu, Hengshu Zhu*, Tong Xu*, Enhong Chen, Chuan Qin, Hui Xiong*, Large-Scale Talent Flow Forecast with Dynamic Latent Factor Model, In Proceedings of The Web Conference 2019 (WWW-2019), San Francisco, CA USA, 2019.
Yuyang Ye, Hengshu Zhu*, Tong Xu, Fuzhen Zhuang, Hui Xiong*, Identifying High Potential Talent: A Neural Network based Dynamic Social Profiling Approach, In Proceedings of the 19th IEEE International Conference on Data Mining (ICDM-2019), 2019.
[读芯术]
Qi Zhang, Tong Xu*, Hengshu Zhu*, Lifu Zhang, Hui Xiong, Enhong Chen, Aftershock Detection with Multi-Scale Description based Neural Network, In Proceedings of the 19th IEEE International Conference on Data Mining (ICDM-2019), 2019.
[读芯术]
Denghui Zhang, Junming Liu, Hengshu Zhu*, Yanchi Liu, Lichen Wang, Pengyang Wang, Hui Xiong*, Job2Vec: Job Title Benchmarking with Collective Multi-View Representation Learning, In Proceedings of the 28th ACM International Conference on Information and Knowledge Management (CIKM-2019), 2019.
Xunxian Wu, Tong Xu, Hengshu Zhu, Le Zhang, Enhong Chen, Hui Xiong, Trend-Aware Tensor Factorization for Job Skill Demand Analysis, In Proceedings of the 28th International Joint Conference on Artificial Intelligence (IJCAI-2019), Macau, China, 2019
Mingfei Teng, Hengshu Zhu*, Chuanren Liu, Chen Zhu, Hui Xiong*, Exploiting the Contagious Effect for Employee Turnover Prediction, In Proceedings of the 33rd AAAI Conference on Artificial Intelligence (AAAI-2019), Honolulu, Hawaii, USA, 2019.
Kai Zhang, Hefu Zhang, Qi Liu,, Hongke Zhao, Hengshu Zhu, Enhong Chen, Interactive Attention Transfer Network for Cross-domain Sentiment Classification, The 33rd AAAI Conference on Artificial Intelligence (AAAI-2019), Honolulu, Hawaii, USA, 2019.
Ying Sun, Hengshu Zhu*, Fuzhen Zhuang*, Jingjing Gu, Qing He, Exploring the Urban Region-of-Interest through the Analysis of Online Map Search Queries, In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2018), London, United Kindom, 2018
[Video]
Chuan Qin, Hengshu Zhu*, Tong Xu, Chen Zhu, Liang Jiang, Enhong Chen, Hui Xiong*, Enhancing Person-Job Fit for Talent Recruitment: An Ability-aware Neural Network Approach, In Proceedings of the 41st International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2018), Ann Arbor, Michigan, USA, 2018.
[雷锋网AI科技评论]
[量子位]
[读芯术]
Dazhong Shen, Hengshu Zhu*, Chen Zhu, Tong Xu, Chao Ma, Hui Xiong*, A Joint Learning Approach to Intelligent Job Interview Assessment, In Proceedings of the 27th International Joint Conference on Artificial Intelligence (IJCAI-2018), Stocholm, Sweden, 2018,
[雷锋网AI科技评论]
[读芯术]
Tong Xu, Hengshu Zhu*, Chen Zhu, Pan Li, Hui Xiong*, Measuring the Popularity of Job Skills in Recruitment Market: A Multi-Criteria Approach, The 32nd AAAI Conference on Artificial Intelligence (AAAI-2018), New Orleans, LA, USA, 2018.
[雷锋网AI科技评论]
[PaperWeekly]
Qingxin Meng, Hengshu Zhu*, Keli Xiao, Hui Xiong*, Intelligent Salary Benchmarking for Talent Recruitment: A Holistic Matrix Factorization Approach, In Proceedings of the 18th IEEE International Conference on Data Mining (ICDM-2018), Singapore, 2018
Liang Zhang, Keli Xiao, Hengshu Zhu, Chuanren Liu, Jingyuan Yang, CADEN: A Context-Aware Deep Embedding Network for Financial Opinions Mining, In Proceedings of the 18th IEEE International Conference on Data Mining (ICDM-2018), Singapore, 2018
Huayu Li, Yong Ge, Hengshu Zhu*, Hui Xiong*, Hongke Zhao, Prospecting the Career Development of Talents: A Survival Analysis Perspective, The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2017), Halifax, Nova Scotia, Canada, 2017.
Yanchi Liu, Chuanren Liu, Xinjiang Lu, Mingfei Teng, Hengshu Zhu, Hui Xiong, Point of Interest Demand Modeling with Human Mobility Patterns, The 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2017), Halifax, Nova Scotia, Canada, 2017.
Hao Lin, Hengshu Zhu*, Yuan Zuo, Chen Zhu, Hui Xiong*, Junjie Wu, Collaborative Company Profiling: Insights from an Employee's Perspective, The 31st AAAI Conference on Artificial Intelligence (AAAI-2017), San Francisco, CA, USA, 2017.
Xunpeng Huang, Le Wu, Enhong Chen, Hengshu Zhu, Qi Liu, Yijun Wang, Incremental Matrix Factorization: A Linear Feature Transformation Perspective, The 26th International Joint Conference on Artificial Intelligence(IJCAI-2017), 2017.
Chao Ma, Chen Zhu, Yanjie Fu, Hengshu Zhu*, Guiquan Liu, Enhong Chen, Social User Profiling: A Social-Aware Topic Modeling Perspective, The 22nd International Conference on Database Systems for Advanced Applications (DASFAA-2017), Suzhou, China, March 27-30, 2017.
Hengshu Zhu, Hui Xiong, Fangshuang Tang, Qi Liu, Yong Ge, Enhong Chen, Yanjie Fu, Days on Market: Measuring the Liquidity of Real Estate Markets, The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2016), San Francisco, CA, USA, 2016.
Chen Zhu, Hengshu Zhu, Hui Xiong, Pengliang Ding, Fang Xie, Recruitment Market Trend Analysis with Sequential Latent Variable Model, The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2016), San Francisco, CA, USA, 2016.
[哈佛商业评论]
[雷锋网AI科技评论]
Tong Xu, Hengshu Zhu, Xiangyu Zhao, Qi Liu, Hao Zhong, Enhong Chen, Hui Xiong, Taxi Driving Behavior Analysis in Latent Vehicle-to-Vehicle Networks: A Social Influence Perspective, The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2016), San Francisco, CA, USA, 2016.
Huayu Li, Yong Ge, Hengshu Zhu, Point-of-Interest Recommendations: Learning Potential Check-ins from Friends, The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2016), San Francisco, CA, USA, 2016.
Huang Xu, Jingyuan Yang, Zhiwen Yu, Hui Xiong, Hengshu Zhu, Talent Circle Detection in Job Transition Networks, The 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2016), San Francisco, CA, USA, 2016.
[哈佛商业评论]
[雷锋网AI科技评论]
Yan Zhu, Hengshu Zhu, Qi Liu, Enhong Chen, Hong Li, Hongke Zhao. Exploring the Procrastination of College Students: A Data-Driven Behavioral Perspective. The 21st International Conference on Database Systems for Advanced Applications (DASFAA-2016), Dallas, Texas, USA, April 16-19, 2016.
Qing Wang, Hengshu Zhu, Wei Hu, Zhiyong Shen, Yuan Yao, Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications, The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015), Sydney, Australia, August 10-13, 2015.
Yanjie Fu, Guannan Liu, Spiros Papadimitriou, Hui Xiong, Yong Ge, Hengshu Zhu, Chen Zhu, Real Estate Ranking via Mixed Land-use Latent Models, The 21st ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2015), Sydney, Australia, August 10-13, 2015.
Guangxiang Zeng, Hengshu Zhu, Qi Liu, Ping Luo, Enhong Chen, Tong Zhang, Matrix Factorization with Scale-Invariant Parameters, The 24th International Joint Conference on Artificial Intelligence (IJCAI-2015), Buenos Aires, Argentina, July 25-31, 2015.
Qi Liu, Xianyu Zeng, Chuanren Liu, Hengshu Zhu, Enhong Chen, Hui Xiong, Xing Xie, Mining Indecisiveness in Customer Behaviors, The 15th IEEE International Conference on Data Mining (ICDM-2015), Atlantic City, NJ, USA, November 14-17, 2015.
Huayu Li, Hengshu Zhu, Yong Ge, Yanjie Fu, Yuan Ge, Personalized TV Recommendation with Mixture Probabilistic Matrix Factorization, In Proceedings of 2015 SIAM International Conference on Data Mining (SDM-2015), Vancouver, British Columbia, Canada, April 30-May 2, 2015.
Tong Xu, Hao Zhong, Hengshu Zhu, Hui Xiong, Enhong Chen, Guannan Liu, Exploring the Impact of Dynamic Mutual Influence on Social Event Participation, In Proceedings of 2015 SIAM International Conference on Data Mining (SDM-2015), Vancouver, Canada, April 30-May 2, 2015.
Guangxiang Zeng, Ping Luo, Enhong Chen, Hui Xiong, Hengshu Zhu, Qi Liu, Convex Matrix Completion: A Trace-Ball Optimization Perspective, In Proceedings of 2015 SIAM International Conference on Data Mining (SDM-2015), Vancouver, British Columbia, Canada, April 30-May 2, 2015.
Huang Xu, Zhiwen Yu, Hui Xiong, Bin Guo, Hengshu Zhu, Learning Career Mobility and Human Activity Patterns for Job Change Analysis, The 15th IEEE International Conference on Data Mining (ICDM-2015), Atlantic City, NJ, USA, November 14-17, 2015.
Chu Guan, Qi Liu, Jingsong Lv, Enhong Chen, Hengshu Zhu, Xin Li, Consolidation: Metric+Active Learning and Its Applications For Cross-domain Recommendation, In Proceedings of the 2015 IEEE/WIC/ACM International Conference on Web Intelligence (WI-IAT 2015), Singapore, December 6-9, 2015.
Hengshu Zhu, Hui Xiong, Yong Ge, Enhong Chen, Mobile App Recommendations with Security and Privacy Awareness, The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) :951-960, New York, NY, USA, August 24-27, 2014.
[PDF]
Meng Qu, Hengshu Zhu, Junming Liu, Guannan Liu, Hui Xiong, A Cost-Effective Recommender System for Taxi Drivers, The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2014) :45-54, New York, NY, USA, August 24-27, 2014.
[PDF]
Biao Chang, Hengshu Zhu, Yong Ge, Enhong Chen, Hui Xiong, Chang Tan, Predicting the Popularity of Online Serials with Autoregressive Models, The 23rd ACM International Conference on Information and Knowledge Management (CIKM-2014) :1339-1348, Shanghai, China, November 3-7, 2014.
[PDF]
Chen Zhu, Hengshu Zhu*, Yong Ge, Enhong Chen, Qi Liu. Tracking the Evolution of Social Emotions: A Time-Aware Topic Modeling Perspective. The 14th IEEE International Conference on Data Mining (ICDM-2014), 697-706, Shenzhen, China, December 14-17, 2014.
[PDF] (Best Paper Nomination)
Bo Jin, Yong Ge, Hengshu Zhu, Guo Li, Hui Xiong, Chao Zhang, Technology Prospecting for High Tech Companies through Patent Mining. The 14th IEEE International Conference on Data Mining (ICDM-2014), Shenzhen, China, December 14-17, 2014.
[PDF]
Fangshuang Tang, Qi Liu, Hengshu Zhu, Enhong Chen, Feida Zhu, Diversified Social Influence Maximization, the 2014 IEEE/ACM International Conference on Advances in Social Network Analysis and Mining (ASONAM-2014) :455 - 459, Beijing, China, August 17-20, 2014.
[PDF]
Hengshu Zhu, Hui Xiong, Yong Ge, Enhong Chen, Ranking Fraud Detection for Mobile Apps: A Holistic View, The 22rd ACM International Conference on Information and Knowledge Management (CIKM-2013): 619-628, San Francisco, CA, USA, October 27-November 1, 2013.
[PDF]
[Data Set]
Xue Bai, Yun Xiong, Yangyong Zhu, Hengshu Zhu, Time Series Representation: A Random Shifting Perspective, the 14th International Conference on Web-Age Information Management (WAIM-2013), 37-50, Beidaihe, Hebei, China, 2013.
[PDF] (Best Student Paper Award)
Kuifei Yu, Hengshu Zhu, Huanhuan Cao, Baoxian Zhang, Enhong Chen, Jilei Tian, Jinghai Rao, Learning to Detect the Subway Station Arrival for Mobile Users. The 14th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL-2013): 49-57, Hefei, Anhui, China, October 20-23, 2013.
[PDF]
Hengshu Zhu, Huanhuan Cao, Enhong Chen, Hui Xiong, Jilei Tian. Exploiting Enriched Contextual Information for Mobile App Classification. The 21st ACM Conference on Information and Knowledge Management (CIKM-2012)：1617-1621, Maui, HI, USA, October 29–November 2, 2012.
[PDF]
Hengshu Zhu, Enhong Chen, Kuifei Yu, Huanhuan Cao, Hui Xiong, Jilei Tian. Mining Personal Context-Aware Preferences for Mobile Users. The 12th IEEE International Conference on Data Mining (ICDM-2012): 1212-1217, Brussels, Belgium, December 10-13, 2012.
[PDF]
Kuifei Yu, Baoxian Zhang, Hengshu Zhu, Huanhuan Cao, Jilei Tian, Towards Personalized Context-Aware Recommendation by Mining Context Logs through Topic Models. The 16th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2012): 431-433, Kuala Lumpur, Malaysia, 2012.
[PDF]
Hengshu Zhu, Huanhuan Cao, Hui Xiong, Enhong Chen, Jilei Tian, Towards Expert Finding by Leveraging Relevant Categories in Authority Ranking, The 20th ACM Conference on Information and Knowledge Management (CIKM-2011): 2221-2224, Glasgow, UK, October 24-28, 2011.
[PDF]
Hengshu Zhu, Enhong Chen, Huanhuan Cao, Finding Experts in Tag Based Knowledge Sharing Communities. the 2011 International Conference on Knowledge Science, Engineering and Management (KSEM-2011): 183-195, Irvine, California, USA, December 12-14, 2011.
[PDF] (Best Student Paper Award)
Patents:
Please visit EPO, USPTO and SIPO for the 100+ patents.
Selected Academic Services
Conference Organizer:
The Pacific Rim International Conference on Artificial Intelligence (PRICAI-2022), Industry Chair
The International Workshop on Talent and Management Computing (TMC-2020,2021), Co-Chair
The KDD Cup 2019 Regular ML Track, Co-organizer
The 2023 International Workshop on Artificial Intelligence for Career Science (AICS-2023), Founding Co-Chair
The 2019 International Workshop on Talent and Management Computing (TMC-2019), Founding Co-Chair
The 28th ACM International Conference on Information and Knowledge Management (CIKM-2019), Session Chair
The 2018 International Workshop on Organizational Behavior and Talent Analytics (OBTA-2018), Founding Co-Chair
The 24th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2018), Session Chair
The 15th IEEE International Conference on Data Mining (ICDM-2015), Session Chair
AC/SPC/PC Member:
The ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD-2015,2016,2018,2019,2020,2021)
The AAAI Conference on Artificial Intelligence (AAAI-2019-2021(SPC),2022-2024(AC))
The International Joint Conference on Artificial Intelligence (IJCAI-2015-2020 (PC),2021-2024(SPC))
The International World Wide Web Conferences (WWW-2020,2021)
The ACM SIGIR International Conference on Research and Development in Information Retrieval (SIGIR-2020,2021)
The IEEE International Conference on Data Mining (ICDM-2015,2017,2018,2019,2020,2021)
The SIAM International Conference on Data Mining (SDM-2015,2016,2017,2018,2019)
The ACM International Conference on Information and Knowledge Management (CIKM-2017,2018,2019,2020,2021)
The ACM International Conference on Web Search and Data Mining (WSDM-2017,2018,2019,2020,2021,2022)
The ACM Recommender Systems Conference (RecSys-2017,2018,2019,2020)
The International Conference on Database Systems for Advanced Applications (DASFAA-2016,2017)
The International AAAI Conference on Web and Social Media (ICWSM-2016,2017)
The International Conference on Big Data Computing and Communications (BIGCOM-2015)
The CCF Conference on Big Data (CCF BigData-2015)
The CCF Conf. on Natural Language Processing and Chinese Computing (NLPCC-2015,2018,2019)
The International Workshop on Mobile Data Mining (MobileDM-2015)
Journal Reviewer:
IEEE Transactions on Knowledge and Data Engineering (TKDE)
IEEE Transactions on Software Engineering (TSE)
IEEE Transactions on Systems, Man, and Cybernetics-System (TSMC-S)
IEEE Transactions on Systems, Man, and Cybernetics-Cybernetics (TSMC-B)
IEEE Transactions on Cybernetics (TC)
IEEE Transactions on Human-Machine Systems (THMS)
ACM Transactions on Intelligent Systems and Technology (TIST)
ACM Transactions on Knowledge Discovery from Data (TKDD)
ACM Transactions on Management Information Systems (TMIS)
ACM Transactions on Multimedia Computing, Communications and Applications (TOMM)
ACM Transactions on Information Systems (TOIS)
Elsevier Pattern Recognition
Springer Knowledge and Information System (KAIS)
Springer World Wide Web (WWWJ)
Springer Geoinformatica
Springer International Journal of Automation and Computing (IJAC)
