Patent ID: 8713190
Filing Date: 2014-04-29
Classification: H04L

Abstract:
1. A method for detecting an anomalous condition in a data stream, comprising: calculating, by a processor, an expected base event count for an event in the data stream for a time interval, wherein the data stream represents data with cross-classified events, wherein each cross-classified event is an event having at least two categories; obtaining, by the processor, an actual event count for the event in the data stream for the time interval; applying, by the processor, a shrinkage factor to a ratio of the actual event count and the expected base event count to obtain an actual estimated event count, wherein the shrinkage factor uses an N parameter family of functions that comprises a family of gamma functions, where N is an integer not greater than two, wherein the shrinkage factor is obtained using a kalman filter gamma-poisson shrinker; and detecting, by the processor, the anomalous condition in accordance with the actual event count and the actual estimated event count.