Abstract: A method for processing time series data comprises: dividing time series data into a plurality of data fragments according to an objective function, the plurality of data fragments having a greatest similarity; in response to determining that at least one data fragment does not satisfy an iteration termination condition, performing following iteration operations on the at least one data fragment; and constructing a time series base pattern library by using a plurality of time series base patterns. The iteration operations includes: using the at least one data fragment as at least one update time series fragment; dividing each update time series fragment into a plurality of update data fragments; using each update data fragment that does not satisfy the iteration termination condition as a new update time series fragment; and using each update data fragment that satisfies the iteration termination condition as a time series base pattern.