Clustering Algorithm for Multiple Data Streams Based on Data Cloud Node

Sa Li; Liang Shan Shao

doi:10.4028/www.scientific.net/AMM.462-463.247

Paper Titles

The Application of Multiple Classifier System for Environmental Audio Classification
p.225

One Hand Tracking Algorithm Based on Behavioral Model of Grasping Object and Particle Filter
p.230

Blind Recognition Algorithm of TT&C Signals of Satellite Based on Fast-ICA Algorithm
p.237

RETRACTED: Analysis of Markov Models
p.243

Clustering Algorithm for Multiple Data Streams Based on Data Cloud Node
p.247

The Blurring and Restoring Process of the Moving Object Images
p.251

An Adaptive Growing Self-Organizing Tree Map for Brain MR Image Segmentation
p.255

A Novel Adaptive Integrated Navigation Filtering Method Based on ARMA/GARCH Model
p.259

2D-3D Medical Image Registration Based on Ant Colony Algorithm
p.267

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 462-463Clustering Algorithm for Multiple Data Streams...

Clustering Algorithm for Multiple Data Streams Based on Data Cloud Node

Abstract:

Multiple data streams clustering aims to clustering multiple data streams according to their similarity while tracking their changes with time . This paper proposes M_SCCStream algorithm based on cloud model. Algorithm introduces data cloud node structure with hierarchical characteristics to represent different granularity data sequence and takes the entropy indicated the degree of data changes. Algorithm finds micro_clustering with the minimum distance and then obtains the clustering result of multiple data streams through calculating the correlation degrees of micro_clustering. The experiment proves that the algorithm has higher quality and stability.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 462-463)

Pages:

247-250

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.462-463.247

Citation:

Cite this paper

Online since:

November 2013

Authors:

Sa Li*, Liang Shan Shao

Keywords:

Clustering, Correlation, Data Cloud Node, Distance, Multiple Data Streams

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

* - Corresponding Author

References

[1] J Yang. Dynamic clustering of evolving streams with a single pass[C]. In: Proc. of IEEE International Conference Data Mini．Washington：IEEE Computer Society，2003: 695-697.

Google Scholar

[2] Beringer J. Hullermeier E. Online clustering of parallel data streams[J]．Data & Knowledge Engineering，2006，58（2）: 180-204.

DOI: 10.1016/j.datak.2005.05.009

Google Scholar

[3] B R Dai, Huang J W, Yeh M Y, et a1. Adaptive clustering for multiple evolving streams[J]．IEEE Transaction on Knowledge and Data Engineering，2006，18（9）: 1166-l180.

DOI: 10.1109/tkde.2006.137

Google Scholar

[4] Sa Li. An data astream clustering algorithms based on cloud model[C]. Engineering and Business Management, Wuhan: 2011（03）: 2651-2654.

Google Scholar