基于灰关联分析的多数据流聚类

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Abstract As a hot research orientation of data stream mining, multiple data stream clustering tracks the evolution of multiple streams and partitions them according to their similarities. In this paper, a multiple data stream clustering approach is proposed, which is based on the combination of grey relational analysis and affinity propagation clustering. A grey relational degree is developed so that the raw data can be compressed into an incrementally updatable grey relational synopsis. The similarity between two data streams is measured by the grey relational degree calculated from the synopsis. Finally, the affinity propagation algorithm is used to cluster the streams. The experiments on the real data sets prove the effectiveness of the new method.

Key words： Clustering Multiple Data Streams Grey Relational Analysis

Received: 27 January 2011

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	GUO Kun
	ZHANG Qi-Shan

Cite this article:

GUO Kun,ZHANG Qi-Shan. Multiple Data Streams Clustering Based on Grey Relational Analysis[J]. , 2011, 24(6): 769-775.

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http://manu46.magtech.com.cn/Jweb_prai/EN/ OR http://manu46.magtech.com.cn/Jweb_prai/EN/Y2011/V24/I6/769

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