Cart (Loading....) | Create Account
Close category search window
 

Digging Deeper into Text Mining: Academics and Agencies Look Toward Unstructured Data

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

1 Author(s)

In an effort to help government officials anticipate significant events such as political unrest, disease outbreaks, or natural disasters, the US government's Intelligence Advanced Research Projects Agency is launching a mass dataset mining effort, hoping to develop technologies that can mine disparate sources such as blogs, search engine results, Internet traffic, webcams, and many others. Researchers in the natural and social sciences have long been doing similar work, however, which might serve to show the current limitations of computational linguistics, especially in trying to discern, on the fly, events that could have significant policy implications.

Published in:

Internet Computing, IEEE  (Volume:16 ,  Issue: 1 )

Date of Publication:

Jan.-Feb. 2012

Need Help?


IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.