Pedersen visit
Raymond Mooney
open slots, please consider signing up to talk to him. He actually get's in
Thurs at noon, so if you would prefer to have a slot Thurs afternoon, just let
me know. Also, faculty, please let me know if you can join dinner Thurs or Fri
evening.
Thanks!
-Ray
---------- Forwarded message ----------
Date: Mon, 13 Sep 2010 13:48:08 -0500
From: Jenna Whitney <j...@cs.utexas.edu>
To: CS-Faculty: ;
Subject: UTCS Colloquium/AI- Ted Pedersen/University of Minnesota,
Duluth:
"The Effect of Different Context Representations on Word Sense
Discriminatio
n in Biomedical Texts" ACES 2.402, Friday, October 8, 2010, 11:00 a.m.
There is a sign-up schedule for this event that can be found at
http://www.cs.utexas.edu/department/webevent/utcs/events/cgi/list_events.cg
i
Type of Talk: UTCS Colloquium/AI
Speaker/Affiliation: Ted Pedersen/University of Minnesota, Duluth
Date/Time: Friday, October 8, 2010, 11:00 a.m.
Location: ACES 2.402
Host: Raymond Mooney
Talk Title: The Effect of Different Context Representations on Word Sense
Discrimination in Biomedical Texts
Talk Abstract: Unsupervised word sense discrimination relies on the idea
that words that occur in similar contexts will have similar meanings. These
techniques cluster multiple contexts in which an ambiguous word occurs, and
the number of clusters discovered indicates the number of senses in which
the ambiguous word is used. One important distinction among these methods is
the underlying means of representing the contexts to be clustered. In this
talk I will compare the efficacy of first--order methods that directly
represent the features that occur in a context with several second--order
methods that use a more indirect representation. I will show that second
order methods that use word by word co--occurrence matrices result in the
highest accuracy and most robust word sense discrimination. These
experiments were conducted with the freely available open--source software
package SenseClusters, using experimental data drawn from MedLine abstracts.
I will also briefly introduce UMLS::Similarity, a freely available
open-source software package that measures the similarity and relatedness of
concepts found in the Unified Medical Language System (UMLS). I will show
how measures from this package can be used to predict the degree of
difficulty in word sense discrimination experiments, and can be used to
perform word sense disambiguation.
-------
Raymond J. Mooney Title: Professor
Department of Computer Science Phone: (512) 471-9558
University of Texas at Austin Fax: (512) 471-8885
1616 Guadalupe, Suite 2.408 E-mail: moo...@cs.utexas.edu
Austin, TX 78701 WWW: http://www.cs.utexas.edu/users/mooney
USA