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	Dynamic symbolization of streaming time series
	Xiaoming Jin ; Jianmin Wang ; Jiaguang Sun
	2010-05-07 ; 2010-05-07
会议名称	Intelligent Data Engineering and Automated Learning - IDEAL 2004. 5th International Conference. Proceedings (Lecture Notes in Comput. Sci. Vol.3177) ; Intelligent Data Engineering and Automated Learning - IDEAL 2004. 5th International Conference. Proceedings ; Exeter, UK ; INSPEC
关键词	Theoretical or Mathematical/ data mining stock markets time series/ dynamic symbolization streaming time series data mining stock market/ C1140Z Other topics in statistics C7120 Financial computing C6130 Data handling techniques
中文摘要	Symbolization of time series is an important preprocessing subroutine for many data mining tasks. However, it is usually difficult, if not impossible, to apply the traditional static symbolization approach on streaming time series, because of either the low efficiency of re-computing the typical sub-series, or the low capability of representing the up-to-date series characters. This paper presents a symbolization method, in which the typical sub-series are dynamically adjusted to fit the up-to-date characters of streaming time series. It works in an incremental form without scanning the whole date set. Experiments on data set from stock market justify the superiority of the proposed method over the traditional ones.
会议录出版者	Springer-Verlag ; Berlin, Germany
语种	英语 ; 英语
内容类型	会议论文
源URL	[http://hdl.handle.net/123456789/16952]
专题	清华大学
推荐引用方式 GB/T 7714	Xiaoming Jin,Jianmin Wang,Jiaguang Sun. Dynamic symbolization of streaming time series[C]. 见:Intelligent Data Engineering and Automated Learning - IDEAL 2004. 5th International Conference. Proceedings (Lecture Notes in Comput. Sci. Vol.3177), Intelligent Data Engineering and Automated Learning - IDEAL 2004. 5th International Conference. Proceedings, Exeter, UK, INSPEC.

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