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Home > People > Jun Xu
Jun Xu

I am an associate researcher at Microsoft Research Asia (MSRA), Information Retrieval and Mining (IRM) Group.

I obtained a B.S. in July 2001 and a Ph.D. in Computer Application and Technology in July 2006, both from Nankai University. My advisor is professor Huang Ya-lou. Thesis: Cost-sensitive Learning of Ranking for Information Retrieval.

I participated in the Microsoft Research Asia Internship Program from September 2003 to December 2005 as a member of Natural Language Computing Group. My mentor is Dr. Hang Li.  

My major research interest includes text mining, machine learning, and web search.

Contact Information

Microsoft Research Asia,
13F, Microsoft Building 2, No. 5 Danling Street, Haidian Distinct
Beijing, China 100080
Email: junxu AT microsoft.com
Tel: +86-10-59173171 
Scholar page: http://scholar.google.com/citations?user=su14mcEAAAAJ&hl=en

Publication

  1. Quan Wang, Zheng Cao, Jun Xu, and Hang Li. Matrix Factorization for Scalable Topic Modeling. Proceedings of the 35th annual international ACM SIGIR conference on Research and development in information retrieval, 2012. (to appear)
  2. Wei Wu, Hang Li, and Jun Xu. Learning Query and Document Similarities from Click-through Bipartite Graph with Metadata. Microsoft Research Technical Report, MSR-TR-2011-126, 2011. (link)
  3. Quan Wang, Jun Xu, Hang Li, and Nick Craswell. Regularized Latent Semantic Indexing. Proceedings of the 34th annual international ACM SIGIR conference on Research and development in information retrieval, Beijing China, 685-694, 2011. (pdf)
  4. Wei Wu, Jun Xu, Hang Li, and Satoshi Oyama. Learning Robust Relevance Model for Search using Kernel Method. Journal of Machine Learning Research (JMLR), 12(May):1429-1458, 2011. (pdf, link)
  5. Jun Xu, Wei Wu, Hang Li, and Gu Xu. A Kernel Approach to Addressing Term Mismatch. Proceedings of the 20th international conference companion on World Wide Web (WWW '11), Hyderabad India, pp. 153-154, 2011. (pdf)
  6. Jun Xu, Hang Li, Tie-Yan Liu, Yisha Peng, Min Lu, and Wei-Ying Ma. Direct Optimization of Evaluation Measures in Learning to Rank. Microsoft Research Technical Report, MSR-TR-2010-171, 2010. (link)
  7. Jun Xu, Hang Li, and Chaoliang Zhong. Relevance Ranking using Kernels. The Sixth Asia Information Retrieval Societies Conference (AIRS 2010), Taiwan, pp. 1-12, 2010. (pdf) Best Paper Award.
  8. Wei Wu, Jun Xu, and Hang Li. Learning Similarity Function between Objects in Heterogeneous Spaces. Microsoft Research Asia Technical Report, MSR-TR-2010-86, 2010. (link)
  9. Wei Wu, Jun Xu, Hang Li, and Satoshi Oyama. Asymmetric Kernel Learning. Microsoft Research Technical Report, MSR-TR-2010-85, 2010. (link)
  10. Weijian Ni, Jun Xu, Yalou Huang, Tong Liu, and Jianye Ge. Acronym Extraction using SVM with Uneven Margins. Proceedings of the 2nd IEEE Symposium on Web Society. Beijing, 2010.
  11. Tao Qin, Tie-Yan Liu, Jun Xu, and Hang Li. LETOR: A Benchmark Collection for Research on Learning to Rank for Information Retrieval. Information Retrieval Journal, 2009. (pdf)
  12. Jun Xu, Hang Li, and Chaoliang Zhong. Relevance Ranking using Kernels. Microsoft Research Technical Report, MSR-TR-2009-80, 2009. (link) 
  13. Weijian Ni, Jun Xu, Hang Li, and Yalou Huang. Group-based Learning — A Boosting Approach. Proceedings of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, California, October 26-30, 2008.(poster pdf)
  14. Tao Qin, Tie-Yan Liu, Jun Xu, and Hang Li. How to Make LETOR More Useful and Reliable. Proceedings of SIGIR 2008 Workshop on Learning to Rank for Information Retrieval (LR4IR 2008), Singapore, 2008. (pdf)
  15. Jun Xu, Tie-Yan Liu, Min Lu, Hang Li, and Wei-Ying Ma. Directly Optimizing Evaluation Measures in Learning to Rank. Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval, Singapore, pp. 107-114, 2008.(pdf)
  16. Yongmei Gao, Yalou Huang, Weijian Ni, and Jun Xu. A Ranking SVM based Algorithm for Automatic Extraction of Acronym. Pattern Recognition and Artificial Intelligence. Vol. 21 No. 2, pp. 186-192, April 2008.
  17. 刘铁岩, 徐君, 李航, 马维英. 为搜索引擎学习最优的排序模型. 中国计算机学会通讯(Communications of CCF), 第3卷, 第10期, 41—45页, 2007年10月.
  18. Jun Xu and Hang Li. AdaRank: A Boosting Algorithm for Information Retrieval. Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval, Amsterdam, The Netherlands, pp. 391-398, 2007. (pdf, tool)
  19. Tie-Yan Liu, Jun Xu, Tao Qin, Wenying Xiong, and Hang Li. LETOR: Benchmarking “Learning to Rank for Information Retrieval”. Proceedings of SIGIR 2007 Workshop on Learning to Rank for Information Retrieval (LR4IR 2007), Amsterdam, The Netherlands, 2007. (pdf)
  20. Jun Xu, Yunbo Cao, Hang Li,  Nick Craswell, and Yalou Huang. Searching Documents Based on Relevance and Type. Proceedings of  the 29th European Conference on Information Retrieval (ECIR2007), Rome, Italy, pp. 629-636, 2007. (pdf)
  21. Jun Xu, Yunbo Cao, Hang Li,  and Yalou Huang. Cost-sensitive Learning of SVM for Ranking. Proceedings of  the 17th European Conference on Machine Learning (ECML2006), Berlin, Germany, pp. 833-840, 2006. (pdf)
  22. Yunbo Cao, Jun Xu, Tie-Yan Liu, Hang Li, Yalou Huang, and Hsiao-Wuen Hon. Adapting ranking SVM to document retrieval. Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, Seattle, Washington, USA, pp. 186-193, 2006. (pdf)
  23. Jun Xu, Yunbo Cao, Hang Li, Min Zhao, and Yalou Huang. A Supervised Learning Approach to Search of Definitions. Journal of Computer Science and Technology (JCST), Vol. 21(3), pp. 439-449, 2006. (pdf) 
  24. Jun Xu and Ya-lou Huang. Using SVM to Extract Acronyms from Text. Soft Computing - A Fusion of Foundations, Methodologies and Applications, Springer Berlin Heidelberg, Vol. 10, 2006. (link, pdf) 
  25. Hang Li, Yunbo Cao, Jun Xu, Yunhua Hu, Shenjie Li, and Dmitriy Meyerzon, A New Approach to Intranet Search Based on Information Extraction. Proceedings of the 14th ACM international conference on Information and knowledge management industry track, Bremen, Germany, pp. 460-468, 2005. (pdf)
  26. Jun Xu, Yunbo Cao,  Hang Li, and Min Zhao. Ranking Definitions with Supervised Learning Methods. Proceedings of the 14th International World Wide Web Conference, Industrial and Practical Experience Track, Chiba, Japan, pp. 811-819, 2005.(pdf)
  27. Jun Xu and Ya-lou Huang. A Machine Learning Approach to Recognizing Acronyms and Their Expansions. Proceedings of the 4th International Conference on Machine Learning and Cybernetics, Guangzhou, China, Vol. 4, pp. 2313-2319, 2005.  (pdf)(ICMLC 2005 Lotfi A Zadeh Outstanding Paper Award) 
  28. Jun Xu, Yalou Huang, and Fei Li. Research on Comparing the Sequential Learning with Batch Learning for K-Means. Computer Science, Vol.31(6), pp.156-158, 193, 2004. 

Technical Talks

  1. Hang Li, Jun Xu. Beyond Bag-of-Words: Machine Learning for Query-Document Matching. SIGIR'12 full day tutorial, 2012. (2 out of 18 submissions. to appear)
  2. Hang Li, Jun Xu. Enhancing Search Relevance : Machine Learning Techniques for Better Matching of Query and Document. WWW'12 tutorial, 2012. (pdf, link)
  3. Hang Li, Jun Xu. Machine Learning for Query Document Matching in Web Search. WSDM'12 tutorial, 2012. (pdf)
  4. Jun Xu. Large Scale Matrix Factorizatioin. invitied talk, Knowledge Engineering Lab, Tsinghua University.
  5. Jun Xu. A Kernel Approach to Matching of Query and Document in Search. invited talk, ACLCLP IR Workshop, 2010. (link)

Downloads

  1. AdaRank: A Boosting Algorithm for Learning to Rank (link)
  2. LETOR: Learning to Rank for Information Retrieval (link)

Patents Filed

  1. Topics in Relevance Ranking Model for Web Search (Granted on Nov. 22, 2011)
  2. Learning Query and Document Similarities from Click-through Bipartite Graph with Metadata
  3. Large Scale Topic Mining using Regularized Latent Semantic Indexing
  4. Query Expansion for Web Search
  5. Directly Optimizing Evaluation Measures in Learning to Rank
  6. Information Retrieval and Ranking
  7. Search Results Ranking using Editing Distance and Document Information
  8. Search by Document Type
  9. A Cost-Sensitive Framework for Supervised Ranking Learning

Professional Activities

  1. Program committee, WSDM 2013
  2. Program committee, SIGIR 2012 poster track
  3. Program Committee, ECIR 2012 and ECIR 2012 poster track (link)
  4. Program Committee, WWW 2012 (link)
  5. Program Committee, WSDM 2012 (link)
  6. Reviewer, IEEE’s Transactions on Knowledge and Data Engineering (TKDE) (link)
  7. Program Committee, SIGIR 2011 Poster (link)
  8. Program Committee, WWW 2011 Content Analysis Track (link)
  9. Program Committee, WSDM 2011 (link)
  10. Program Committee, AIRS 2010 (link)
  11. Reviewer, ACM Transactions on Asian Language Information Processing(link)
  12. Reviewer, ACM Transactions on Intelligent Systems and Technology (link)
  13. Reviewer, Electronic Commerce Research and Applications (link)
  14. Reviewer, posters for SIGIR 2010 (link)
  15. Program Committee, SIGIR 2010 (link)
  16. Program Committee, SIGIR 2009 Workshop Learning to Rank for Information Retrieval L2R4IR'09 (link)
  17. Program Committee, EMNLP 2009, information retrieval and question answering (link)
  18. Program Committee, ACL-IJCNLP 2009, Information Retrieval (link)
  19. Reviewer, Information Retrieval (link)
  20. Program Committee, EMNLP 2008, Document Collections and Information Retrieval (link)
  21. Program Committee, SIGIR 2008 Workshop Learning to Rank for Information Retrieval(link)
  22. Reviewer, The 3rd International Joint Conference on Natural Language Processing (IJCNLP 2008)
  23. Reviewer, Journal of Software (link)

Links

Hang Li, Tie-Yan Liu, Yunhua Hu, Bin Gao, Tao Qin, Jie Tang
Information Retrieval and Mining Group, IIP Lab, Nankai University

Modified by Jun Xu on May. 3, 2012