Progressive and Iterative Approaches for Time Series Averaging

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).

• Type: Journal
• Year: 2015
• Where: PKDD
• Authors: Saeid Soheily-Khah, Ahlame Douzal Chouakria, Éric Gaussier
• Keywords: Data Mining, PKDD 2015