Approximations to Magic: Finding Unusual Medical Time Series

	This Article
	Subscribers, please Login Purchase article: $19 PDF IEEE Xplore Subscribers RSS feed
	Share
	Email this Article to a friend
	Bibliographic References
	ASCII Text BibTex RefWorks Procite/RefMan/Endnote
	Add to:
	Digg Furl Spurl Blink Simpy Google Del.icio.us Y!MyWeb
	Search
	Similar Articles Articles by Jessica Lin Articles by Eamonn Keogh Articles by Ada Fu Articles by Helga Van Herle

18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05)

Dublin, Ireland

June 23-June 24

ISBN: 0-7695-2355-2

	ASCII Text	x
	Jessica Lin, Eamonn Keogh, Ada Fu, Helga Van Herle, "Approximations to Magic: Finding Unusual Medical Time Series," Computer-Based Medical Systems, IEEE Symposium on, pp. 329-334, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005.

	BibTex	x
	@article{ 10.1109/CBMS.2005.34, author = {Jessica Lin and Eamonn Keogh and Ada Fu and Helga Van Herle}, title = {Approximations to Magic: Finding Unusual Medical Time Series}, journal ={Computer-Based Medical Systems, IEEE Symposium on}, volume = {0}, year = {2005}, issn = {1063-7125}, pages = {329-334}, doi = {http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.34}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, }

	RefWorks Procite/RefMan/Endnote	x
	TY - CONF JO - Computer-Based Medical Systems, IEEE Symposium on TI - Approximations to Magic: Finding Unusual Medical Time Series SN - 1063-7125 SP329 EP334 A1 - Jessica Lin, A1 - Eamonn Keogh, A1 - Ada Fu, A1 - Helga Van Herle, PY - 2005 KW - null VL - 0 JA - Computer-Based Medical Systems, IEEE Symposium on ER -

Jessica Lin, University of California at Riverside

Eamonn Keogh, University of California at Riverside

Ada Fu, Chinese University of Hong Kong

Helga Van Herle, University of California at Los Angeles

DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/CBMS.2005.34

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.

Citation:

Jessica Lin, Eamonn Keogh, Ada Fu, Helga Van Herle, "Approximations to Magic: Finding Unusual Medical Time Series," cbms, pp.329-334, 18th IEEE Symposium on Computer-Based Medical Systems (CBMS'05), 2005

Peer Review Notice | Give Us Feedback

Usage of this product signifies your acceptance of the Terms of Use.