Patent ID: 9197511
Filing Date: 2015-11-24
Classification: H04L

Abstract:
1. A method, comprising: performing, by one or more computing devices: obtaining time-series data for a given time range, wherein the time-series data comprises values for a network-site analytics metric for each of a plurality of sequential time steps across the given time range; generating a predictive model for the network-site analytics metric based on at least a segment of the time-series data, wherein the predictive model performs time series analysis by taking recognized cycles into consideration by applying a mathematical model that represents the recognized cycles; using the predictive model to predict different expected value ranges based on different confidence levels for the network-site analytics metric for a next time step after the segment; based on detection of actual values that are outside of the different expected value ranges for different numbers of consecutive occurrences, determining whether a particular actual value for the network-site analytics metric for the next time step is an anomalous value; and indicating the particular actual value as the anomalous value in a report display for the network-site analytics metric.