DocumentCode :
3549354
Title :
Approximations to magic: finding unusual medical time series
Author :
Lin, Jessica ; Keogh, Eamonn ; Fu, Ada ; Van Herle, Helga
Author_Institution :
California Univ., Riverside, CA, USA
fYear :
2005
fDate :
23-24 June 2005
Firstpage :
329
Lastpage :
334
Abstract :
In this work we introduce the new problem of finding time series discords. Time series discords are subsequences of longer time series that are maximally different to all the rest of the time series subsequences. They thus capture the sense of the most unusual subsequence within a time series. While the brute force algorithm to discover time series discords is quadratic in the length of the time series, we show a simple algorithm that is 3 to 4 orders of magnitude faster than brute force, while guaranteed to produce identical results.
Keywords :
approximation theory; electrocardiography; time series; ECG; approximation; force algorithm; medical time series; time sequence; Biomedical equipment; Data mining; Detectors; Electrocardiography; Euclidean distance; Heart rate variability; Humans; Medical services; Sampling methods;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Computer-Based Medical Systems, 2005. Proceedings. 18th IEEE Symposium on
ISSN :
1063-7125
Print_ISBN :
0-7695-2355-2
Type :
conf
DOI :
10.1109/CBMS.2005.34
Filename :
1467711
Link To Document :
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