By Topic

Detecting New and Emerging Events from Textual Sources

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

2 Author(s)
Roberts, K. ; Human Language Technol. Res. Inst., Univ. of Texas at Dallas, Richardson, TX, USA ; Harabagiu, S.M.

Recognizing new and emerging events in a stream of news documents requires understanding the semantic structure of news reported in natural language. New event detection (NED) is the task of recognizing when a news document discusses a completely novel event. To be successful at this task, we argue a NED method must extract and represent the type of event and its participants as well as the temporal and spatial properties of the event. Our NED methods produce a 25% cost reduction over a bag-of-words baseline and a 13% cost reduction over an existing state-of-the-art approach. Additionally, we discuss our method for recognizing emerging events: the tracking and categorization of unexpected or novel events.

Published in:

Semantic Computing (ICSC), 2011 Fifth IEEE International Conference on

Date of Conference:

18-21 Sept. 2011