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Home > People > Hang Li
Hang Li

 

I am senior researcher and research manager of Information Retrieval and Mining Group at Microsoft Research Asia. I am also adjunct professor of Peking University, Nanjing University, Xian Jiaotong University, and Nankai University. I am co-director of the MS joint lab at PKU and member of the machine learning lab at NJU.

I joined Microsoft Research in June 2001. Prior to that, I worked at the Research Laboratories of NEC Corporation.

I obtained a B.S. in Electrical Engineering from Kyoto University in 1988 and a M.S. in Computer Science from Kyoto University in 1990. I earned my Ph.D. in Computer Science from the University of Tokyo in 1998.

I am interested in statistical learning, information retrieval, data mining, and natural language processing.

Contact Information

Microsoft Research Asia
4F, Sigma Center
No. 49 Zhichun Road, Haidian District
Beijing, China 100190
Email: hangli at microsoft dot com
Tel: (86-10)58963177
Fax: (86-10)88097306

Talks

  • Hang Li, Learning to Rank, ACML 2009 Tutorial, Nov. 2, 2009. (pdf)
  • Hang Li, Learning to Rank, ACL-IJCNLP 2009 Tutorial, Aug. 2, 2009. (pdf)
  • Hang Li, Exploring New Frontiers of Search, Univerisity of Massachusetts Amherst, June 19, 2009. (pdf)
  • Hang Li, Web Information Retrieval, University of Science and Technology of China, May 26, 2009. (pdf)

Recent Publications

  • Wei Chen, Tie-Yan Liu, Yanyan Lan, Zhiming Ma, Hang Li, Ranking Measures and Loss Functions in Learning to Rank. Advances in Neural Information Processing Systems 22 (NIPS’09), to appear.
  • Fen Xia, Tie-Yan Liu, Hang Li, Statistical Consistency of Top-k Ranking. Advances in Neural Information Processing Systems 22 (NIPS’09), to appear.
  • Bin Gao, Tie-Yan Liu, Zhiming Ma, Taifeng Wang, Hang Li, A General Markov Framework for Page Importance Computation. Proc. of CIKM’09 (short paper), to appear, 2009. (pdf)
  • Yuting Liu, Tie-Yan Liu, Zhiming Ma, and Hang Li. A Framework to Compute Page Importance based on User Behaviors, Information Retrieval Journal, to appear.
  • Jiafeng Guo, Gu Xu, Xueqi Cheng, Hang Li, Named Entity Recognition in Query. Proc. of SIGIR 2009, 267-274. (pdf)
  • Xin Jiang, Yunhua Hu, Hang Li, A Ranking Approach to Keyphrase Extraction. Proc. of SIGIR 2009 (poster), 756-757. (pdf)
  • Gu Xu, Shuanghong Yang, Hang Li, Named Entity Mining from Click-Through Log Using Weakly Supervised Latent Dirichlet Allocation. Proc. of KDD 2009, 1365-1374. (pdf)
  • Bin Zhou, Daxin Jiang, Jian Pei, Hang Li, OLAP on Search Logs: An Infrastructure Supporting Data-Driven Applications in Search Engines. Proc. of KDD 2009, 1395-1404. (pdf)
  • Yanyan Lan, Tie-Yan Liu, Zhi-Ming Ma, Hang Li, Generalization Analysis of Listwise Learning to Rank Algorithms. Proc. of ICML 2009, 577-584. (pdf)
  • Ming Li, Hang Li, Zhi-Hua Zhou, Semi-Supervised Document Retrieval. Information Processing and Managment, 45, 341-355. (pdf)
  • Huanhuan Cao, Daxin Jiang, Jian Pei, Enhong Chen, Hang Li, Towards Context-aware Search by Learning a Very Large Variable Length Hidden Markov Model from Search Logs. Proc. of WWW 2009, 191-200. (pdf)
  • Qi He, Daxin Jiang, Zhen Liao, Steven C. H. Hoi, Kuiyu Chang, Ee-Peng Lim, Hang Li, Web Query Recommendation via Sequential Query Prediction. Proc. of ICDE 2009, 1443-1454. (pdf)
  • Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Hang Li, Global Ranking Using Continuous Conditional Random Fields, Advances in Neural Information Processing Systems 21, 2009, 1281-1288. (pdf)
  • Congkai Sun, Bin Gao, Zhenfu Cao, and Hang Li, HTM: A Topic Model for Hypertexts, Prof. of EMNLP 2008, 514-522. (pdf)
  • Huanhuan Cao, Daxin Jiang, Jian Pei, Qi He, Zhen Liao, Enhohng Chen, Hang Li, Context-Aware Query Suggestion by Mining Click-Through and Session Data, Proc. of KDD 2008, 875-883. SIGKDD’08 Best Application Paper Award. (pdf)
  • Fen Xia, Tie-Yan Liu, Jue Wang, Wensheng Zhang, Hang Li, Listwise Approach to Learning to Rank –Theory and Algorithm, Proc. of ICML 2008, 1192-1199. (pdf)
  • Yanyan Lan, Tie-Yan Liu, Tao Qin, Zhiming Ma, Hang Li, Query Level Stability and Generalization in Learning to Rank, Proc. of ICML 2008, 512-519. (pdf)
  • Yuting Liu, Bin Gao, Tie-Yan Liu, Ying Zhang, Zhiming Ma, Shuyuan He, Hang Li, BrowseRank: Letting Users Vote for Page Importance, Proc. of SIGIR 2008, 451-458. SIGIR’08 Best Student Paper Award. (pdf)
  • Xiubo Geng, Tie-Yan Liu, Tao Qin, Andrew Arnold, Hang Li, Heung-Yeung Shum, Query Dependent Ranking with K Nearest Neighbor, Proc. of SIGIR 2008, 115-122. (pdf)
  • Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, Wei-Ying Ma, Directly Optimizing Evaluation Measures in Learning to Rank, Proc. of SIGIR 2008, 107-114. (pdf)
  • Jiafeng Guo, Gu Xu, Hang Li, Xueqi Cheng, A Unified and Discriminative Model for Query Refinement, Proc. of SIGIR 2008, 379-386. (pdf)
  • Rong Jin, Hamed Valizadegan, Hang Li, Ranking Refinement and Its Application to Information Retrieval, Proc. of WWW 2008, 397-406. (pdf)
  • Tao Qin, Tie-Yan Liu, Xu-Dong Zhang, De-Sheng Wang, Wen-Ying Xiong, Hang Li, Learning to Rank Relational Objects and Its Application to Web Search, Proc. of WWW 2008, 407-416. (pdf)
  • Gu Xu, Hang Li, Wei-Ying Ma, Fora: Leveraging the Power of Internet Communities for Question Answering, Proc. of WWW 2008 Workshop on QA Web. (pdf)
  • Xiaonan Ji, Gu Xu, James Bailey, and Hang Li, Mining, Ranking, and Using Acronym Patterns, Prof. of APWeb-2008, 371-382. (pdf)
  • Tao Qin, Xu-Dong Zhang, Ming-Feng Tsai, De-Sheng Wang, Tie-Yan Liu, Hang Li, Query-level Loss Functions for Information Retrieval, Information Processing and Management, 44, 838-855, 2008.  (pdf)