By Topic

Text analysis and knowledge mining

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
$33 $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)
Tetsuya Nasukawa ; IBM Research - Tokyo, 1623-14 Shimo-tsuruma, Yamato-shi, Kanagawa-ken, 242-8502, Japan

As the use of IT systems expands, growing amounts of textual data are being generated, stored, and searched. This trend is widely believed to be causing information overload. Although the increase of accessible data is intended to increase our knowledge and yield insights for better actions, the data glut is making it hard to find meaning. Natural Language Processing (NLP) is a key technology to exploit text data, so applications for NLP are increasing rapidly. Such applications often exploit text mining, but they involve a broad range of NLP technologies as the applications develop. This new trend is generating new demands for NLP that require more research.

Published in:

Natural Language Processing, 2009. SNLP '09. Eighth International Symposium on

Date of Conference:

20-22 Oct. 2009