Abstract: The invention relates to a method for characterizing time series. The method includes obtaining a time series that includes data points for consecutive time intervals, decomposing the time series into a trend component, a seasonal component, and a residual component, and clustering the seasonal component into a number of clusters. Each of the consecutive time intervals is assigned to one of the clusters based on a level of the data points of the seasonality component in the time interval. The method further includes labeling one of the clusters as baseline with the baseline cluster containing more time intervals than any one of the other clusters, determining cluster labels for the other clusters based on the level of the data points of the time intervals assigned to the other clusters; and for each time interval, storing the corresponding cluster label in a vector.