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[nl-uiuc] [Fwd: DISTINGUISHED LECTURESHIP SERIES, Eugene Charniak, Feb. 5]


Chronological Thread 
  • From: "Margaret M. Fleck" <mfleck AT cs.uiuc.edu>
  • To: nl-uiuc AT cs.uiuc.edu
  • Subject: [nl-uiuc] [Fwd: DISTINGUISHED LECTURESHIP SERIES, Eugene Charniak, Feb. 5]
  • Date: Wed, 31 Jan 2007 11:13:08 -0600
  • List-archive: <http://lists.cs.uiuc.edu/pipermail/nl-uiuc>
  • List-id: Natural language research announcements <nl-uiuc.cs.uiuc.edu>



-------- Original Message --------
Subject: DISTINGUISHED LECTURESHIP SERIES, Eugene Charniak, Feb. 5
Date: Wed, 31 Jan 2007 10:56:07 -0600
From: Erna A Amerman
<erna AT cs.uiuc.edu>
To:
<ifaculty AT cs.uiuc.edu>
CC:
<clerical AT cs.uiuc.edu>



Prof. Gerald DeJong is the host assisted by Ronda Pellegrini at rpellegr AT cs.uiuc.edu.







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





*/ /*

*/DISTINGUISHED LECTURESHIP SERIES/*

*/ (and Graduate Seminar)/*








*/Recent Results in Parsing/*


*/ /**//*


Eugene Charniak

Department of Computer Science


Brown University



February 5 (Monday), 2007 at 4:00 p.m.

1404 Siebel Center for Computer Science




Parsing is the problem of mapping a string (in, say, English) to a phrase structure. It is important because it gives us a first rough cut at meaning. During the 1990s there was a flurry of new results using statistical techniques that gave us our first robust parsers ready for every-day use. While there has been continued results since then, the practical parsers at the start of 2005 were no better than what has available in 2000. The first part of the talk will recap this ancient history.



The last two years, however, have seen a dramatic turn-around with error rates decreasing by 25%. The second and third parts of the talk describe the two techniques responsible for this state of affairs: discriminative reranking and self training. We also show that the latest results seem to be less corpus specific than the previous results. (That is, they carry over to text corpora reasonably different than those upon which they were trained.





Bio:

Eugene Charniak is University Professor of Computer Science and Cognitive Science at Brown University and past chair of the Department of Computer Science. He received his A.B. degree in Physics from University of Chicago, and a Ph.D. from M.I.T. in Computer Science. He has published four books the most recent being Statistical Language Learning. He is a Fellow of the American Association of Artificial Intelligence and was previously a Councilor of the organization. His research has always been in the area of language understanding or technologies which relate to it. Over the last 15 years he has been interested in statistical techniques for parsing, speech recognition, and other areas of language processing.





Reception after the talk in the 2^nd Floor Atrium of Siebel Center.





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Attachment: POSTER Feb. 5, DLS Eugene Charniak (DeJong-RP).doc
Description: MS-Word document



  • [nl-uiuc] [Fwd: DISTINGUISHED LECTURESHIP SERIES, Eugene Charniak, Feb. 5], Margaret M. Fleck, 01/31/2007

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