Method and system for detecting anomalies in web analytics data
First Claim
1. A computer-implemented method for identifying events of interest in web analytics data, the method comprising:
- at a computer server having one or more processors and memory for storing programs to be executed by the one or more processors;
storing web analytics data for a web page in a device, wherein the web analytics data comprises a plurality of prior time-value pairs, each time-value pair including a value of one of a plurality of attributes associated with the web page and a time associated with the value;
collecting a new time-value pair for a particular attribute of the plurality of attributes, the new time-value pair including a new value associated with the web page and a new time when the new value was determined;
estimating a predicted value for the particular attribute and an associated error-variance at the new time for the predicted value by applying a forecasting model to the plurality of prior time-value pairs in respective subsets of the web analytics data; and
for the new time-value pair and the particular attribute, determining a significance factor such that, when the error-variance is multiplied by the significance factor, the value of the new time-value pair is inside the factored error-variance of the predicted value.
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Accused Products
Abstract
A server system stores web analytics data for a web page in a device. The web analytics data comprises a plurality of prior time-value pairs, each pair including a value of an attribute associated with the web page and a time associated with the value. For a particular attribute, the server system collects a new time-value pair including a new value associated with the web page and a new time indicating when the value was determined. The server system estimates a predicted value for the attribute and an associated error-variance at the new time by applying a forecasting model to the prior time-value pairs in respective subsets of the web analytics data. The collected new time-value pair is tagged if its value is outside the error variance of the predicted value for the particular attribute.
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Citations
27 Claims
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1. A computer-implemented method for identifying events of interest in web analytics data, the method comprising:
at a computer server having one or more processors and memory for storing programs to be executed by the one or more processors; storing web analytics data for a web page in a device, wherein the web analytics data comprises a plurality of prior time-value pairs, each time-value pair including a value of one of a plurality of attributes associated with the web page and a time associated with the value; collecting a new time-value pair for a particular attribute of the plurality of attributes, the new time-value pair including a new value associated with the web page and a new time when the new value was determined; estimating a predicted value for the particular attribute and an associated error-variance at the new time for the predicted value by applying a forecasting model to the plurality of prior time-value pairs in respective subsets of the web analytics data; and for the new time-value pair and the particular attribute, determining a significance factor such that, when the error-variance is multiplied by the significance factor, the value of the new time-value pair is inside the factored error-variance of the predicted value. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 26, 27)
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13. A server system for identifying anomalies in web analytics data, wherein the server system is connected to one or more client devices through a network, the server system comprising:
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one or more processors for executing programs; and memory to store data and to store one or more programs to be executed by the one or more processors, the one or more programs comprising instructions for; storing web analytics data for a web page in a device, wherein the web analytics data comprises a plurality of prior time-value pairs, each time-value pair including a value of one of a plurality of attributes associated with the web page and a time associated with the value; collecting a new time-value pair for a particular attribute of the plurality of attributes, the new time-value pair including a new value associated with the web page and a new time when the value was determined; estimating a predicted value for the attribute and an associated error-variance at the new time for the predicted value by applying a forecasting model to the plurality of prior time-value pairs in respective subsets of the web analytics data; and for the new time-value pair and the particular attribute, determining a significance factor such that, when the error-variance is multiplied by the significance factor, the value of the new time-value pair is inside the factored error-variance of the predicted value. - View Dependent Claims (14, 15, 16, 17, 18, 19, 20)
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21. A non-transitory computer readable-storage medium storing one or more programs for execution by one or more processors, the one or more programs comprising instructions for:
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storing web analytics data for a web page in a device, wherein the web analytics data comprises a plurality of prior time-value pairs, each time-value pair including a value of one of a plurality of attributes associated with the web page and a time associated with the value; collecting a new time-value pair for the particular attribute, the new time-value pair including a new value associated with the web page and a new time when the value was determined; estimating a predicted value for the attribute and associated error-variance at the new time for the predicted value by applying a forecasting model to the plurality of prior time-value pairs in respective subsets of the web analytics data; and for the new time-value pair and the particular attribute, determining a significance factor such that, when the error-variance is multiplied by the significance factor, the value of the new time-value pair is inside the factored error-variance of the predicted value. - View Dependent Claims (22, 23, 24, 25)
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Specification