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[nl-uiuc] FW: Data Science Summer Institute Talk, Raymond Mooney, July 11th at 3:15


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  • From: "Fleck, Margaret M" <mfleck AT cs.uiuc.edu>
  • To: "nl-uiuc AT cs.uiuc.edu" <nl-uiuc AT cs.uiuc.edu>
  • Subject: [nl-uiuc] FW: Data Science Summer Institute Talk, Raymond Mooney, July 11th at 3:15
  • Date: Wed, 9 Jul 2008 10:08:16 -0500
  • Accept-language: en-US
  • Acceptlanguage: en-US
  • List-archive: <http://lists.cs.uiuc.edu/pipermail/nl-uiuc>
  • List-id: Natural language research announcements <nl-uiuc.cs.uiuc.edu>


________________________________________
From: Schaefer, Melinda M
[mschaefr AT cs.uiuc.edu]
Sent: Wednesday, July 09, 2008 9:37 AM
To:
ifaculty AT cs.uiuc.edu;

cs-grads AT cs.uiuc.edu
Cc:
mschaefr AT uiuc.edu;
King, Robin Brian
Subject: Data Science Summer Institute Talk, Raymond Mooney, July 11th at 3:15

University of Illinois at Urbana-Champaign
Department of Computer Science
The Thomas M. Siebel Center for Computer Science
201 North Goodwin Avenue
Urbana, Illinois 61801-2302 USA


Data Science Summer Institute Talk


Learning Language from its Perceptual Context


Raymond J. Mooney, Professor
Department of Computer Science
University of Texas at Austin
Friday, July 11, 2008 at 3:15 P.M.
2405 Siebel Center for Computer Science



Abstract:

Current systems that learn to process natural language require laboriously
constructed human-annotated training data. Ideally, a computer would be able
to acquire language like a child by being exposed to linguistic input in the
context of a relevant but ambiguous perceptual environment. As a step in this
direction, we present a system that learns to sportscast simulated soccer
games by example. The training data consists of textual human commentaries on
Robocup simulation games. A set of possible meanings for each comment is
automatically constructed from game event traces. Our previously developed
systems for learning to parse and generate natural language (KRISP and WASP)
were augmented to learn from this data and then commentate novel games. The
system is evaluated based on its ability to parse sentences into correct
meanings and generate accurate descriptions of game events. Human evaluation
was also conducted on the overall quality of the generated sportscasts and
compared to human-generated commentaries.
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 150
published research papers, primarily in the areas of machine learning and
natural language processing. He is the current President of the International
Machine Learning Soceity, was program co-chair for the 2006 AAAI Conference
on Artificial Intelligence, general chair of the 2005 Human Language
Technology Conference and Conference on Empirical Methods in Natural Language
Processing, and co-chair of the 1990 International Conference on Machine
Learning. He is a Fellow of the American Association for Artificial
Intelligence and recipient of best paper awards from the National Conference
on Artificial Intelligence, the SIGKDD International Conference on Knowledge
Discovery and Data Mining, and the Annual Meeting of the Association for
Computational Linguistics. His recent research has focused on learning for
natural-language processing, text mining for bioinformatics, statistical
relational learning, and transfer learning.


Melinda Schaefer
Department of Computer Science
University of Illinois, Urbana/Champaign
201 N. Goodwin Ave
2232 Siebel Center, MC-258
Urbana, IL 61801
(217)333-6454
mschaefr AT uiuc.edu<mailto:mschaefr AT uiuc.edu>






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