中文摘要：

针对目前已有的时间序列数据分段方法多侧重于静态数据的分段现状,根据时间序列流数据的变化情况,分析数据流的状态,提出一种有限自动机的分段方法,它通过分析时间序列流中数据所处的状态,进而发现其中的变化点,并以变化点作为段的两端,从而完成时间序列的分段。实验表明,这种方法能够有效地对高速时间序列流进行分段,保证了分段的效果和质量。

英文摘要：

Aiming at the disadvantage of existing segmenting methods for time series mainly focus on the static data, this paper proposed a method for segmenting time series stream, namely, a deterministic finite automata,according to time-series stream data changes, analyzing the data flow state. By analyzing the state of the time-series data stream, the changes in it could be found and thus complete the time series segmentation, taking change point as the segment ends. Extensive empirical experiments, both on synthetic and real datasets, show that the approach achieves great effectiveness on the high speed time series stream, and the quality of the segments is assured.