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.
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2011, Vol. 24 
