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| Machine Learning Seminar Series | ||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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| Date: | December 12, 2005 |
| Time: | 10:00 AM - 11:00 AM |
| Location: | 1305 Newell-Simon Hall |
| Speaker: | Raymond J. Mooney Professor |
| Title: | Learning for Semantic Parsing of Natural Language |
| Abstract: | Semantic parsing is the task of mapping a natural-language sentence into a detailed formal representation of its meaning. This talk presents a summary of our research on learning semantic parsers from corpora of sentences annotated with formal representations. Our original work employed inductive-logic programming methods to learn deterministic symbolic parsers, our more recent work has applied current techniques from statistical syntactic parsing, machine translation, and support vector machines using string kernels to learn more robust semantic parsers. We present results on learning to interpret natural language database queries and robot commands (Robocup coaching instructions). |
| Speaker Bio: | Raymond J. Mooney is a Professor in the Department of Computer Sciences at the University of Texas at Austin. He received his Ph.D. in 1988 from the University of Illinois at Urbana/Champaign. He is an author of over 100 published research papers, primarily in the area of machine learning. He is program co-chair for the 2006 National Conference on Artificial Intelligence, a recent general chair of the 2005 Human Language Technology Conference and Conference on Empirical Methods in Natural Language Processing, a former co-chair of the 1990 International Conference on Machine Learning, a former editor of the Machine Learning journal, and a Fellow of the American Association for Artificial Intelligence. His recent research has focused on learning for natural-language processing, text mining, statistical relational learning, semi-supervised learning, bioinformatics, and autonomic computing. |