Approximate Clustering on Data Streams Using Discrete Cosine Transform
- Resource Type
- Article
- Authors
- Feng Yu; Damalie Oyana; Wen-Chi Hou; Michael Wainer
- Source
- JIPS(Journal of Information Processing Systems), 6(1), 15, pp.67-78 Mar, 2010
- Subject
- 컴퓨터학
- Language
- English
- ISSN
- 2092-805X
1976-913X
In this study, a clustering algorithm that uses DCT transformed data is presented. The algorithm is a grid density-based clustering algorithm that can identify clusters of arbitrary shape. Streaming data are transformed and reconstructed as needed for clustering. Experimental results show that DCT is able to approximate a data distribution efficiently using only a small number of coefficients and preserve the clusters well. The grid based clustering algorithm works well with DCT transformed data, demonstrating the viability of DCT for data stream clustering applications.