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

A fast subspace partition clustering algorithm for high dimensional 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

2 Author(s)
Zhongping Zhang ; Coll. of Inf. Sci. & Eng., Yanshan Univ., Qinhuangdao, China ; Hao Wang

Data stream clustering is an important research problem in data stream mining. However, clustering arbitrary shapes over high dimensional data streams has not been well addressed. In this paper, we propose a fast subspace partition data streams clustering algorithm, which adopts two-phased clustering framework. In the online component, the extension of adjacent unit (E-unit), which has common edge or vertex with dense units, is presented. Moreover, the improved CD-tree lattice structure is introduced to store the information of non-empty units, maintain the position relationships among units, and keep the affiliation between dense units (D-units) and E-units. Outdated units which need to be faded are performed by decayed function, so that the corresponding microclusters are maintained dynamically. In the offline component, the final clusters are generated according to all the micro-clusters by searching D-units in radius range. Experimental results show that SPDStream has higher clustering quality than CluStream which can not generate clusters of arbitrary shapes. Furthermore, our approach has better scalability with different dimensionality and different partition granularity.

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.