Abstract : Averaging a set of time series is a major topic for many temporal data mining tasks as summarization, extracting prototype or clustering. Time series averaging should deal with the tricky multiple temporal alignment problem; a still challenging issue in various domains. This work compares the major progressive and iterative averaging time series methods under dynamic time warping (dtw).
https://hal.archives-ouvertes.fr/hal-01208451
Contributeur : Ahlame Douzal
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Soumis le : vendredi 2 octobre 2015 - 15:48:17
Dernière modification le : jeudi 11 janvier 2018 - 06:27:15
Saeid Soheily-Khah, Ahlame Douzal-Chouakria, Eric Gaussier. Progressive and Iterative Approaches for Time Series Averaging. ECML-PKDD, Sep 2015, Porto, Portugal. 〈hal-01208451〉
