Abstract: An apparatus is provided for identifying representation. The representation is obtained for heterogeneous time series data. The apparatus comprises a model training device and a data classification device. Based on the requirements of compression rate and information loss, a most suitable time series representation is found out for a specific time series data. In particular, the model training device assesses each item of training time series data to evaluate the performance of various representations for thus identifying the most suitable representation for each item of the specific training time series data; and, then, the training time series data are clustered and the most representative time series data for each clustered data is determined.