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

A three-step clustering algorithm over an evolving data stream

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)
Liu Li-xiong ; Nat. Digital Switching Syst. Eng. & Technol. Res. Center, Zhengzhou, China ; Kang Jing ; Guo Yun-fei ; Huang Hai

Distinguishing potential new cluster data from outliers is a main problem in mining new pattern from evolving data streams. Meanwhile, all the clustering algorithms inherited from CluStream framework are distribution-based learning which are realized via a sliding window, so this problem becomes more obvious. This paper proposes a three-step clustering algorithm, rDenStream, based on DenStream, which includes outlier retrospect learning. During rDenStream clustering, dropped micro-clusters are stored on outside memory temporarily, and when a new cluster is discovered, these micro-clusters are learned retrospectively to find formally inaccurately-discarded data, which will improve the accuracy of the new cluster. rDenStream has important meaning in applications which require high-accuracy clustering from evolving data. Considering the data stream feature in NIDS, this paper models the arriving time of new pattern data as non-homogeneous Poisson distribution. Experiments over standard data set show its advantage over other methods in the early phase of new pattern discovery.

Published in:

Intelligent Computing and Intelligent Systems, 2009. ICIS 2009. IEEE International Conference on  (Volume:1 )

Date of Conference:

20-22 Nov. 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.