Our mission is to harvest and curate the wealth of knowledge encoded in text: the people, content, things, connections between them, and activities around them. We mobilize research and advanced technology projects for the Technology arm of MSR (MSR-T) by adapting, developing and integrating state-of-the-art technology from areas such as NLP, text mining, machine learning, knowledge extraction, and knowledge representation, while building end to end interactive knowledge experiences in close collaboration with partners across MSR and product teams.
Patrick conducts research in large-scale natural language processing, text mining, and knowledge acquisition. Prior he served as a Research Manager at Yahoo! Labs, and as a Research Assistant Professor at the USC Information Sciences Institute. In 2003, he received a Ph.D. in Computing Science from the University of Alberta in Edmonton, Canada.
Michael has been a member of the NLP group in MSR for more than 17 years. He has done research and collaborated with colleagues across MSR in a wide range of NLP areas, such as grammar engineering, natural language generation, sentiment detection, automatic grammar error detection/correction, social media analysis, salience and intent modeling.
Xiaolin's main research area is in mining and understanding user behavior and user experience in various information systems, such as search, social media, and social networks. Prior to joining MSR, she was an applied researcher in Bing focusing on the domain of online metrics. Before joining Microsoft, she was a postdoctoral scholar at Stanford University from 2009 to 2011. She obtained her PhD in Computer Science and Engineering from the University of Michigan in 2009.
Claudia Leacock, Martin Chodorow, Michael Gamon, and Joel Tetreault, Automated Grammatical Error Detection for Language Learners, Second Edition, Morgan & Claypool, March 2014.
Michael Gamon, Tae Yano, Xinying Song, Johnson Apacible, and Patrick Pantel, Identifying Salient Entities in Web Pages, ACM International Conference on Information and Knowledge Management (CIKM), 1 November 2013.
Patrick Pantel, Michael Gamon, Omar Alonso, and Kevin Haas, Social Annotations: Utility and Prediction Modeling. , ACM, August 2012.
Munmun De Choudhury, Michael Gamon, and Scott Counts, Happy, Nervous or Surprised? Classification of Human Affective States in Social Media, Association for the Advancement of Artificial Intelligence, June 2012.
Thomas Lin, Patrick Pantel, Michael Gamon, Anitha Kannan, and Ariel Fuxman, Active Objects: Actions for Entity-Centric Search, in World Wide Web, ACM, April 2012.
Yoav Artzi, Patrick Pantel, and Michael Gamon, Predicting Responses to Microblog Posts, ACL/SIGPARSE, 2012.
Patrick Pantel and Ariel Fuxman, Jigs and Lures: Associating Web Queries with Strongly-Typed Entities, in Proceedings of Association for Computational Linguistics - Human Language Technology (ACL-HLT-11), June 2011.
Cristian Danescu-Niculescu-Mizil, Michael Gamon, and Susan Dumais, Mark My Words! Linguistic Style Accommodation in Social Media., in Proceedings of WWW 2011, Hyderabad, India., ACM, 1 April 2011.
Eric Crestan and Patrick Pantel, Web-Scale Table Census and Classification, in Proceedings of Web Search and Data Mining (WSDM-11), 2011.
Arnd Christian König, Michael Gamon, and Qiang Wu, Click-Through Prediction for News Queries , in 32nd Annual ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2009), Association for Computing Machinery, Inc., July 2009.
Simon H. Corston-Oliver, Eric Ringger, Michael Gamon, and Richard Campbell, Integration of Email and Task Lists, American Association for Artificial Intelligence , July 2004.