An Improved WaveCluster Algorithm Based on ICA

Author

Li, Xiaoli ; Luo, Min

Author_Institution

Modern Educ. Technol. Center, Nantong Univ., Nantong, China

fYear

2009

fDate

24-26 Sept. 2009

Firstpage

1

Lastpage

5

Abstract

In this paper, we introduce an improved WaveCluster algorithm, which can deal with the high-dimensional data issue (IWCA algorithm for short). The algorithm combines the advantages of ICA algorithm that can reduce the dimension of database. By this means, we can not only cluster the high-dimensional data, but also reduce the time complexities. Finally, the experimental results on KDD Cup 1999 data sets show that IWCA algorithm can efficiently find clusters in high-dimensional data space.

Keywords

computational complexity; independent component analysis; pattern clustering; ICA algorithm; KDD Cup 1999 data; database; high-dimensional data space; improved WaveCluster algorithm; independent component analysis; time complexity; Algorithm design and analysis; Clustering algorithms; Covariance matrix; Databases; Educational technology; Feature extraction; Independent component analysis; Partitioning algorithms; Principal component analysis; Space technology;

fLanguage

English

Publisher

ieee

Conference_Titel

Wireless Communications, Networking and Mobile Computing, 2009. WiCom '09. 5th International Conference on

Conference_Location

Beijing

Print_ISBN

978-1-4244-3692-7

Electronic_ISBN

978-1-4244-3693-4

Type

conf

DOI

10.1109/WICOM.2009.5302493

Filename

5302493