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Big physics experiments can collect terabytes (even petabytes) of data under continuous or long pulse basis. The measurement systems that follow the temporal evolution of physical quantities translate their observations into very large time-series data and video-movies. This article describes a universal and automatic technique to recognize and locate inside waveforms and video-films both signal segments with data of potential interest for specific investigations and singular events. The method is based on regression estimations of the signals using support vector machines. A reduced number of the samples is shown as outliers in the regression process and these samples allow the identification of both special signatures and singular points. Results are given with the database of the JET fusion device: location of sawteeth in soft x-ray signals to automate the plasma incremental diffusivity computation, identification of plasma disruptive behaviors with its automatic time instant determination, and, finally, recognition of potential interesting plasma events from infrared video-movies.