1 Introduction
Research about mining in the data stream environment has flourished recently [1], [2], [3], [4], [5], [6], [7], [8]. In addition to those that consider a data stream at a time, more and more emerging applications are involved in monitoring multiple data streams concurrently. Such applications include online stock market trades, call detail records in telecommunication, data collection in sensor network, and ATM operations in banks to name a few. We are able to find out interesting and useful knowledge by analyzing the relationship among these multiple data streams. Therefore, mining multiple data streams has attracted an increasing amount of attention from related researchers. To discover the cross-relationship among streams, one way is to calculate the correlation between streams and report the stream pairs with high correlation [9], [10], [11]. Another one is to do a similarity pattern query between multiple data streams [9], [12]. Moreover, several works are reported on applying the clustering technique to multiple data streams [13], [14], [15], [16].