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

Machine Learning Trend Anticipation by Text Mining Methodology Based on SSCI Database

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

4 Author(s)
Chiang, J.K. ; Dept. of Manage. Inf. Syst., Nat. Chengchi Univ., Taipei, Taiwan ; Wen-Chin Wu ; Wei-Cheng Liao ; Chi-Yen Yin

This paper is providing an introduction to the text mining methodology. There are many different researches which applying machine learning to improve its management application efficiency in various domains. This research is utilizing text mining technology, including "two step auto-clustering", "glossaries aggregation", "TF-IDF" and so on, which collecting the homogeneous glossaries from articles, guiding to the literature cluster analysis based on the Social Science Citation Index (SSCI) database. The result discovered that the research domains of artificial intelligence, document pattern and financial related are the most prosperous fields on machine learning application, it is leading by information technology development progressing, Web 2.0 is also a boost to research morale. All of these will become a power for important developing direction on machine learning in near future.

Published in:

INC, IMS and IDC, 2009. NCM '09. Fifth International Joint Conference on

Date of Conference:

25-27 Aug. 2009

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.