By Topic

Mining Text with Pimiento

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)
Adeva, J.J.G. ; Sch. of Electr. & Inf. Eng., Sydney Univ., NSW ; Calvo, R.

To perform analysis, decision-making, and knowledge management tasks, information systems use an increasing amount of unstructured information in the form of text. This data influx, in turn, has spawned a need to improve the text-mining technologies required for information retrieval, filtering, and classification. This article compares some of the options available. In particular, the authors focus on Pimiento, a new object-oriented application framework that lets developers create distributed applications that use machine-learning and statistical techniques to automatically process documents

Published in:

Internet Computing, IEEE  (Volume:10 ,  Issue: 4 )