Event clustering and event series characterization based on expected frequency

摘要

A method for clustering time stamps in time series data includes receiving a one-dimensional array of ordered timestamps and an expected frequency; determining a set of time intervals; determining a first binary array that indicates whether each time interval in the set of time intervals is greater than or less than the expected frequency; determining a second binary array of differences between a corresponding pair of adjacent elements of the first binary array; appending an ith timestamp to one of a set of opening interval bounds, a set of closing interval bounds, or a set of isolated points; merging the set of set of opening interval bounds and the set of closing interval bounds into a set of cluster intervals τ; and outputting the set of cluster intervals and the set of isolated points.