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ICDE
2003
IEEE

Dynamic Clustering of Evolving Streams with a Single Pass

9 years 11 months ago
Dynamic Clustering of Evolving Streams with a Single Pass
Stream data is common in many applications, e.g., stock quotes, merchandize sales record, system logs, etc.. It is of great importance to analyze these stream data. As one of the most commonly used techniques, clustering on streams can help to detect and monitor correlations among streams. Due to the unique nature of streaming data, direct application of most existing clustering algorithms fails to deliver efficient results. In this project, we introduce a novel model of stream cluster which employs a weighted distance measure. In addition, we device a novel efficient algorithm which can effectively discover all stream clusters.
Jiong Yang
Added 01 Nov 2009
Updated 01 Nov 2009
Type Conference
Year 2003
Where ICDE
Authors Jiong Yang
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