Patrick Pantel is a member of the Knowledge and Language Group at Microsoft Research, conducting research in large-scale natural language processing, text mining, and knowledge acquisition. Prior he served as a Senior 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.
- Jianfeng Gao, Patrick Pantel, Michael Gamon, Xiaodong He, Li Deng, and Yelong Shen, Modeling Interestingness with Deep Neural Networks, EMNLP, October 2014.
- Michael Gamon, Arjun Mukherjee, and Patrick Pantel, Predicting Interesting Things in Text, ACL – Association for Computational Linguistics, August 2014.
- Patrick Pantel, Michael Gamon, and Ariel Fuxman, Smart Selection, ACL – Association for Computational Linguistics, 6 June 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.
- Michael Gamon, Tae Yano, Xinying Song, Johnson Apacible, and Patrick Pantel, Understanding Document Aboutness Step One: Identifying Salient Entities, no. MSR-TR-2013-73, 27 October 2013.
- Hassan Sajjad, Patrick Pantel, and Michael Gamon, Underspecified Query Refinement via Natural, ACL/SIGPARSE, December 2012.
- Patrick Pantel, Michael Gamon, Omar Alonso, and Kevin Haas, Social Annotations: Utility and Prediction Modeling. , ACM, August 2012.
- Patrick Pantel, Thomas Lin, and Michael Gamon, Mining Entity Types from Query Logs via User Intent Modeling, Association for Computational Linguistics, July 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.
Full list of publications and technology demos are available at my personal site.