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

A semi-supervised weighted clustering framework facing to hybrid attributes data streams

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)
Xinquan Chen ; Coll. of Math. & Comput. Sci., Shangrao Normal Univ., Shangrao, China

In order to solve weighted clustering analysis problem of infinite hybrid attributes data streams in finite space, it presents a weighted clustering and evolution analysis framework. This framework is based on decision-tree classify of little sample using a semi-supervised strategy. In order to record some necessary information of cluster group, it gives a definition of cluster feature vector group of hybrid attributes data streams. In order to update the feature weight group, it presents an adaptive optimization method of configuring feature weight group. It gives some necessary discuss about weighted clustering and evolution analysis framework, which is important to implement this framework. This framework can get better results sometimes.

Published in:

Intelligent Control and Automation (WCICA), 2010 8th World Congress on

Date of Conference:

7-9 July 2010

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.