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 proceedingConference PaperResearchpeer-review

    106 Citations (Scopus)
    Original languageEnglish
    Title of host publicationProceedings,14th IEEE International Conference on Data Mining (ICDM 2014)
    EditorsRavi Kumar, Hannu Toivonen, Jian Pei, Joshua Zhexue Huang, Xindong Wu
    Place of PublicationLos Alamitos CA USA
    PublisherIEEE, Institute of Electrical and Electronics Engineers
    Pages470 - 479
    Number of pages10
    ISBN (Print)9781479943029
    DOIs
    Publication statusPublished - 2014
    EventIEEE International Conference on Data Mining 2014 - Shenzhen, China
    Duration: 14 Dec 201417 Dec 2014
    Conference number: 14th
    http://ieeexplore.ieee.org/xpl/mostRecentIssue.jsp?punumber=7022262 (Conference Proceedings)

    Conference

    ConferenceIEEE International Conference on Data Mining 2014
    Abbreviated titleICDM 2014
    CountryChina
    CityShenzhen
    Period14/12/1417/12/14
    Internet address

    Cite this

    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). Los Alamitos CA USA: IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/ICDM.2014.27
    Petitjean, Francois ; Forestier, Germain ; Webb, Geoffrey Ian ; Nicholson, Ann Elizabeth ; Chen, Yanping ; Keogh, Eamonn. / 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
    @inproceedings{4c17656e68f0466eae9214b68c100f86,
    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",

    }

    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; Nicholson, Ann Elizabeth; Chen, Yanping; Keogh, Eamonn.

    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 proceedingConference PaperResearchpeer-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

    PY - 2014

    Y1 - 2014

    UR - http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7023364

    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

    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 https://doi.org/10.1109/ICDM.2014.27