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Selected Publications (by Subjective Area)

# Mining Enterprise Data (Talent and Management Computing):

  1. 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]
  2. 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]
  3. 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]
  4. 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.
  5. Chen Zhu, Hengshu Zhu, Hui Xiong, Pengliang Ding, Fang Xie, Trend Analysis of Recruitment Market 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]
  6. 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]
  7. 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]
  8. 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.
  9. 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.
  10. 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.
  11. 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.
  12. 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.
  13. 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]
  14. 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]
  15. 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
  16. Chuan Qin, Hengshu Zhu, Tong Xu, Chen Zhu, 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.
  17. 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, ACM Transactions on Management Information Systems (ACM TMIS), 2018. [MIT Technology Review] [Fast Company] [Tech Xplore]
  18. 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.
  19. 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]
  20. 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
  21. 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.

# Mining Spatial-Temporal Data (Mobile Computing, Urban Computing):

  1. 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]
  2. 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.
  3. 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.
  4. 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.
  5. 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.
  6. 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.
  7. 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.
  8. 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]
  9. 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.
  10. 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
  11. Hengshu Zhu, Enhong Chen, Hui Xiong, Huanhuan Cao, Jiilei Tian, Mobile App Classification with Enriched Contextual Information, IEEE Transactions on Mobile Computing (IEEE TMC) 13(7): 1550-1563, 2014. [PDF]
  12. 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]

# Mining Business Data (Business Intelligence, Markets, FinTech):

  1. 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
  2. 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]
  3. 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]
  4. Hengshu Zhu, Chuanren Liu, Yong Ge, Hui Xiong, Enhong Chen, Popularity Modeling for Mobile Apps: A Sequential Approach, IEEE Transactions on Cybernetics (IEEE TC), 45(7): 1303-1314, 2015. [PDF] [Data Set]
  5. 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]
  6. 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.
  7. 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.
  8. 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]
  9. 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]
  10. 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
  11. 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.
  12. 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.

  13. 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.

# Mining Social Data (Social Computing, Social Good):

  1. 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 Nature Scientific Reports , 2020. [Paper]
  2. Dazhong Shen, Qi Zhang, Tong Xu, Hengshu Zhu, Wenjia Zhao, Zikai Yin, Peilun Zhou, Lihua Fang, Enhong Chen, Hui Xiong, Machine Learning-enhanced Realistic Framework for Real-time Seismic Monitoring - The Winning Solution of the 2017 International Aftershock Detection Contest, Technical Report, arXiv:1911.09275, 2019
  3. 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.
  4. 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]
  5. 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)
  6. 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.
  7. Zikai Yin, Tong Xu, Hengshu Zhu, Chen Zhu, Enhong Chen, Hui Xiong, Matching of Social Events and Users: A Two-Way Selection Perspective, Springer World Wide Web (Springer WWW) , 2019.
  8. Enhong Chen, Guangxiang Zeng, Ping Luo, Hengshu Zhu, Jilei Tian, Hui Xiong, Discerning Individual Interests and Shared Interests for Social User Profiling, Springer World Wide Web (Springer WWW) , 20(2): 417-435, March 2017.
  9. Hengshu Zhu, Enhong Chen, Hui Xiong, Huanhuan Cao, Jilei Tian, Ranking User Authority with Relevant Knowledge Categories for Expert Finding, Springer World Wide Web (Springer WWW), 17:1081-1107, 2014. [PDF]
  10. Chen Zhu, Hengshu Zhu, Yong Ge, Enhong Chen, Qi Liu, Tong Xu, Hui Xiong, Tracking the Evolution of Social Emotions with Topic Models, Springer Knowledge and Information System Journal (Springer KAIS) , 47(3): 517-544, 2016.
  11. Tong Xu, Hengshu Zhu, Enhong Chen, Baoxing Huai, Hui Xiong, Jilei Tian, Learning to Annotate via Social Interaction Analytics, Springer Knowledge and Information System Journal (Springer KAIS) : 41(2): 251-276, 2014 [PDF]
  12. 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.
  13. 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]
  14. 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)

# Data Mining Methodology (Recommender System, NLP, Knowledge Management):

  1. Fuzhen Zhuang, Zhiyuan Qi, Keyu Duan, Dongbo Xi, Yongchun Zhu, Hengshu Zhu, Hui Xiong, Qing He, A Comprehensive Survey on Transfer Learning, Technical Report, arXiv:1911.02685, 2019
  2. 秦川, 祝恒书, 庄福振, 郭庆宇, 张琦, 张乐, 王超, 陈恩红, 熊辉, 基于知识图谱的推荐系统研究综述, 《中国科学: 信息科学》, 2020.
  3. 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
  4. 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
  5. 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.
  6. 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.
  7. 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.
  8. 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.
  9. 怀宝兴, 宝腾飞, 祝恒书, 刘淇, 一种基于概率主题模型的命名实体链接方法, 《软件学报》, 2014. (CCDM-2014 最佳学生论文) [PDF]