Text Mining, Search and Navigation Research
The Text Mining, Search, and Navigation group performs research in information retrieval, machine learning, data mining, computational linguistics, and human-computer interaction. We work on new algorithms, and with large datasets, with the overall goal of enhancing the user's online experience.
Charter
Our charter is to explore and develop principled methods for improving online services such as Search and Advertising.
We are deeply involved with the academic community and we work closely with the Microsoft product teams. The challenges the product teams face present wonderful opportunities for research and the algorithms and techniques we develop open up new opportunities for product features. We are happiest when we both achieve significant academic impact and succeed in helping to positively impact millions of people in their use of the Web, intranets, email, and other online services.
Primary contact: Chris J.C. Burges
People
Publications
- Arnd Christian König, Michael Gamon, and Qiang Wu, Click-Through Prediction for News Queries , in SIGIR'09: the 32nd Annual ACM SIGIR Conference on Research and Development in Information Retrieval, Association for Computing Machinery, Inc., July 2009
- Sonal Gupta, Mikhail Bilenko, and Matthew Richardson, Catching the Drift: Learning Broad Matches from Clickthrough Data, in Proceedings of the 15th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2009), Association for Computing Machinery, Inc., June 2009
- Arnd Christian König, Kenneth Church, and Martin Markov, A Data Structure for Sponsored Search, in 24th International Conference on Data Engineering (ICDE), IEEE Computer Society, 29 March 2009
- Matthew Richardson, Learning about the World through Long-Term Query Logs, in ACM Transactions on the Web, vol. 2, no. 4, Association for Computing Machinery, Inc., October 2008
- Z. Zhuang and S. Cucerzan, Exploiting Semantic Query Context to Improve Search Ranking, in The 2nd IEEE International Conference on Semantic Computing, July 2008
- Ryen White, Matthew Richardson, Mikhail Bilenko, and Allison Heath, Enhancing Web Search by Promoting Multiple Search Engine Use , in Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2008), Association for Computing Machinery, Inc., July 2008
- Lilyana Mihalkova and Matthew Richardson, Speeding up Inference in Statistical Relational Learning by Clustering Similar Query Literals, no. MSR-TR-2008-72, May 2008
- M. Bilenko and R. W. White, Mining the Search Trails of Surfing Crowds: Identifying Relevant Websites From User Activity, in Proceedings of the 17th International World Wide Web Conference (WWW-2008), January 2008
- M. Bilenko, R. W. White, M. Richardson, and G. C. Murray, Talking the Talk vs. Walking the Walk: Salience of Information Needs in Querying vs. Browsing, in Proceedings of the 31st Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2008), 2008
- P. Singla and M. Richardson, Yes, There is a Correlation - From Social Networks to Personal Behavior on the Web, in Proceedings of the 17th International World Wide Web Conference (WWW-2008), January 2008
- W. Dakka and S. Cucerzan, Augmenting Wikipedia with Named Entity Tags, in Proceedings of IJCNLP 2008, January 2008
- Surajit Chaudhuri, Kenneth Church, Arnd Christian König, and Liying Sui, Heavy-Tailed Distributions and Multi-Keyword Queries , in 30th ACM SIGIR International Conference on Research & Developement on Information Retreival, Association for Computing Machinery, Inc., July 2007
- D. Zhou and C.J.C. Burges, Spectral Clustering and Transductive Learning with Multiple Views, in Proceedings of the 24th International Conference on Machine Learning, January 2007
- A. Jain, S. Cucerzan, and S. Azzam, Acronym-Expansion Recognition and Ranking on the Web, in Proceedings of IEEE-IRI 2007, January 2007
- M. Richardson, E. Dominowska, and R. Ragno, Predicting Clicks: Estimating the Click-Through Rate for New Ads, in Proceedings of the 16th International World Wide Web Conference(WWW-2007), January 2007
- R. W. White, M. Bilenko, and S. Cucerzan, Studying the use of popular destinations to enhance web search interaction, in Proceedings of the 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR-2007), January 2007
- M. Richardson, A. Prakash, and E. Brill, Beyond PageRank: Machine Learning for Static Ranking, in Proceedings of the 15th International World Wide Web Conference(WWW-2006), January 2006
- Christopher J.C. Burges and John C. Platt, Semi-Supervised Learning with Conditional Harmonic Mixing, in Semi-Supervised Learning, MIT Press, 2006
- S. Cucerzan and E. Agichtein, Predicting Accuracy of Extracting Information from Unstructured Text Collections, in The ACM Conference on Information and Knowledge Management, Association for Computing Machinery, Inc., September 2005
- S. Cucerzan and E. Brill, Spelling correction as an iterative process that exploits the collective knowledge of web users, in Proceedings of EMNLP 2004, July 2004
