Dynamic time warping averaging of time series allows faster and more accurate classification

Francois Petitjean; Germain Forestier; Geoffrey Ian Webb; Ann Elizabeth Nicholson; Yanping Chen; Eamonn Keogh

doi:10.1109/ICDM.2014.27

Dynamic time warping averaging of time series allows faster and more accurate classification

Francois Petitjean, Germain Forestier, Geoffrey Ian Webb, Ann Elizabeth Nicholson, Yanping Chen, Eamonn Keogh

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

Original language	English
Title of host publication	Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014)
Editors	Ravi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu
Place of Publication	Los Alamitos CA USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	470 - 479
Number of pages	10
ISBN (Print)	9781479943029
DOIs	https://doi.org/10.1109/ICDM.2014.27
Publication status	Published - 2014
Event	IEEE International Conference on Data Mining 2014 - Shenzhen, China Duration: 14 Dec 2014 → 17 Dec 2014 Conference number: 14th http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7022262 (Conference Proceedings)

Conference

Conference	IEEE International Conference on Data Mining 2014
Abbreviated title	ICDM 2014
Country/Territory	China
City	Shenzhen
Period	14/12/14 → 17/12/14
Internet address	http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7022262 (Conference Proceedings)

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10.1109/ICDM.2014.27

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Petitjean, F., Forestier, G., Webb, G. I., Nicholson, A. E., Chen, Y., & Keogh, E. (2014). Dynamic time warping averaging of time series allows faster and more accurate classification. In R. Kumar, H. Toivonen, J. Pei, J. Z. Huang, & X. Wu (Eds.), Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014) (pp. 470 - 479). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICDM.2014.27

Petitjean, Francois ; Forestier, Germain ; Webb, Geoffrey Ian et al. / Dynamic time warping averaging of time series allows faster and more accurate classification. Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014). editor / Ravi Kumar ; Hannu Toivonen ; Jian Pei ; Joshua Zhexue Huang ; Xindong Wu. Los Alamitos CA USA : IEEE, Institute of Electrical and Electronics Engineers, 2014. pp. 470 - 479

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title = "Dynamic time warping averaging of time series allows faster and more accurate classification",

author = "Francois Petitjean and Germain Forestier and Webb, \{Geoffrey Ian\} and Nicholson, \{Ann Elizabeth\} and Yanping Chen and Eamonn Keogh",

year = "2014",

doi = "10.1109/ICDM.2014.27",

language = "English",

isbn = "9781479943029",

pages = "470 -- 479",

editor = "Ravi Kumar and Hannu Toivonen and Jian Pei and Huang, \{Joshua Zhexue\} and Xindong Wu",

booktitle = "Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014)",

publisher = "IEEE, Institute of Electrical and Electronics Engineers",

address = "United States of America",

note = "IEEE International Conference on Data Mining 2014, ICDM 2014 ; Conference date: 14-12-2014 Through 17-12-2014",

url = "http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7022262",

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Petitjean, F, Forestier, G, Webb, GI , Nicholson, AE, Chen, Y & Keogh, E 2014, Dynamic time warping averaging of time series allows faster and more accurate classification. in R Kumar, H Toivonen, J Pei, JZ Huang & X Wu (eds), Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014). IEEE, Institute of Electrical and Electronics Engineers, Los Alamitos CA USA, pp. 470 - 479, IEEE International Conference on Data Mining 2014, Shenzhen, China, 14/12/14. https://doi.org/10.1109/ICDM.2014.27

Dynamic time warping averaging of time series allows faster and more accurate classification. / Petitjean, Francois; Forestier, Germain; Webb, Geoffrey Ian et al.
Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014). ed. / Ravi Kumar; Hannu Toivonen; Jian Pei; Joshua Zhexue Huang; Xindong Wu. Los Alamitos CA USA: IEEE, Institute of Electrical and Electronics Engineers, 2014. p. 470 - 479.

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review

TY - GEN

T1 - Dynamic time warping averaging of time series allows faster and more accurate classification

AU - Petitjean, Francois

AU - Forestier, Germain

AU - Webb, Geoffrey Ian

AU - Nicholson, Ann Elizabeth

AU - Chen, Yanping

AU - Keogh, Eamonn

N1 - Conference code: 14th

PY - 2014

Y1 - 2014

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UR - https://www.scopus.com/pages/publications/84936941169

U2 - 10.1109/ICDM.2014.27

DO - 10.1109/ICDM.2014.27

M3 - Conference Paper

SN - 9781479943029

SP - 470

EP - 479

BT - Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014)

A2 - Kumar, Ravi

A2 - Toivonen, Hannu

A2 - Pei, Jian

A2 - Huang, Joshua Zhexue

A2 - Wu, Xindong

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Los Alamitos CA USA

T2 - IEEE International Conference on Data Mining 2014

Y2 - 14 December 2014 through 17 December 2014

ER -

Petitjean F, Forestier G, Webb GI , Nicholson AE, Chen Y, Keogh E. Dynamic time warping averaging of time series allows faster and more accurate classification. In Kumar R, Toivonen H, Pei J, Huang JZ, Wu X, editors, Proceedings,14th IEEE International Conference on Data Mining (ICDM 2014). Los Alamitos CA USA: IEEE, Institute of Electrical and Electronics Engineers. 2014. p. 470 - 479 doi: 10.1109/ICDM.2014.27

Dynamic time warping averaging of time series allows faster and more accurate classification

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