System Maintenance:
There may be intermittent impact on performance while updates are in progress. We apologize for the inconvenience.
By Topic

Phrase detection and the associative memory neural network

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)
Murphy, R.C. ; Dept. of Comput. Sci. & Eng., Notre Dame Univ., USA

This paper describes the use of a novel associative memory neural network architecture to perform unsupervised phrase detection in a large, unstructured, English text corpus. To significantly increase the difficulty associated with processing the text corpus, the network is exposed to over 270 thousand Web pages from the .edu domain with no textual substitution or alteration (for spelling, grammar, etc.). The corpus, consisting of 150M words, is represented as a string of sparse tokens and phrase detection is performed through the use of the unique information theoretic quantity of mutual significance.

Published in:

Neural Networks, 2003. Proceedings of the International Joint Conference on  (Volume:4 )

Date of Conference:

20-24 July 2003