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A Grid and Density-Based Clustering Algorithm for Processing Data Stream

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3 Author(s)
Chen Jia ; State Key Lab. of Software Eng., Wuhan Univ., Wuhan ; Chengyu Tan ; Ai Yong

This paper proposes DD-Stream, a framework for density-based clustering stream data. The algorithm adopts a density decaying technique to capture the evolving data stream and extracts the boundary point of grid by the DCQ-means algorithm. Our method resolving the problem of evolving automatic clustering of real-time data streams, cannot only find arbitrary shaped clusters with noise, but also avoid the clustering quality problems caused by discarding the boundary point of grid, our algorithm has better scalability in processing large-scale and high dimensional stream data as well.

Published in:

Genetic and Evolutionary Computing, 2008. WGEC '08. Second International Conference on

Date of Conference:

25-26 Sept. 2008