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

A New Approach of Data Clustering by Improved ACA with Fuzzy Similarity

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

3 Author(s)

An approach of data clustering based on improved ACA with fuzzy similarity (ACA-Cluster) is presented. Combined with the global distribution and gradual evolution of improved ACA, we assign distribution rate as heuristic function to accelerate convergence. Performance of the algorithm is compared with K-means and LF to demonstrate efficiency and quality.

Published in:

Data, Privacy, and E-Commerce, 2007. ISDPE 2007. The First International Symposium on

Date of Conference:

1-3 Nov. 2007

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.