Natural language research announcements

["Samdani, Rajhans" <rsamdan2 AT illinois.edu>]

Dear all,

This is a gentle reminder for today's AIIS talk by Prof. Ellen Riloff 
(http://www.cs.utah.edu/~riloff/)
from Utah. Following are the details of her talk (**Notice the change in time 
and venue
from the usual AIIS seminars**)

When: **Monday, June 17, 3-4 pm**

Where: **3401** Siebel Center

TITLE: Finding Event Information: Multi-faceted Event Recognition and
Discourse-Guided Extraction

ABSTRACT:
Extracting information about events from text poses several challenges
for NLP systems. Finding documents about a specific type of event is
difficult because of the wide variety of event phrases and because
context often determines the nature of an event.  Finding the entities
and objects that play important roles in an event is also challenging
due to the complexity of narrative texts and discourse phenomena.

I will present recent work at the University of Utah on event
recognition and event extraction. We have developed a multi-faceted
approach to event recognition that identifies documents about a
specific type of event by searching for event phrases as well as
defining characteristics (facets) of the event type. We use a novel
bootstrapping algorithm to automatically learn the necessary
dictionaries of event phrases, agent terms, and purpose (reason)
phrases for civil unrest events. Experimental results show that
multi-faceted event recognition with these bootstrapped dictionaries
yields high accuracy.  I will also present a new bottom-up
architecture for extracting role filler information from event
descriptions.  Our extraction model includes a structured sentence
classifier to identify event-related contexts based on lexical
associations, discourse relations, and role filler distributions
within and across sentences. This approach yields state-of-the-art
performance on the MUC-4 terrorism data set, achieving substantially
higher precision than previous systems.

BIO:
Ellen Riloff is an Associate Professor of Computer Science in the
School of Computing at the University of Utah. Her primary research
areas are information extraction, semantics, sentiment analysis, and
coreference resolution.  A major emphasis of her research has been
automatically acquiring the knowledge needed for natural language
processing using bootstrapping methods that learn from unannotated
texts. She has served on the NAACL Executive Board, Human Language
Technology (HLT) Advisory Board, Computational Linguistics Editorial
Board, Transactions of the Association for Computational Linguistics
(TACL) Editorial Board, and as Program Co-Chair for the NAACL HLT 2012
and CoNLL 2004 conferences.

Hope you will attend.
Best,
Rajhans