Patent ID: 8682816

Claim:
A computer-implemented method for identifying significant events in time series data, the method comprising: storing in a database time series data for a data source, wherein the time series data comprises a plurality of time-value pairs, each pair including a value of one or more attributes associated with the data source and a time associated with the value; for a particular attribute, generating a plurality of forecasting models for characterizing the time-value pairs, each forecasting model including an estimated attribute value and a corresponding error-variance; and for a time-value pair associated with the particular attribute: determining a plurality of differences between the value of the time-value pair and the attribute values estimated by the plurality of forecasting models; determining a significance factor such that each of the plurality of differences for at least a subset of the forecasting models is smaller than the corresponding error-variance multiplied by the significance factor; and identifying the time-value pair as a significant event in response to a determination that the significance factor exceeds a significance threshold for the particular attribute.