Traffic Predictor for Network-Accessible Information Modules
First Claim
1. A method for estimating the performance of an information package, comprisingreceiving one or more values of respective attributes of an information package;
- obtaining, for at least one of the one or more attributes, a buzz value characterizing the level of interest in the attribute based on analysis of on-line user search activity; and
providing one or more attributes and one or more buzz values as input parameters to a regression model to yield a numerical value characterizing an estimated performance of the information package, wherein the regression model is based on historical performance of a set of previous information packages relative to the one or more attributes, and provides the coefficients for the input parameters to the estimated performance of the information package.
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Abstract
Methods, apparatuses and systems directed to predicting the performance of an information package or module presented on a network addressable resource, such as a web page. The present invention, in some particular implementations, relies on regression models that utilize statistical measures of user interest in terms, concepts and other subject matter as revealed in on-line search activity of a pool of users. In a particular implementation, a model receives as inputs a plurality of attribute values corresponding to an information package or module (including one or more statistical measures of interest) and outputs an estimated click-thru rate.
58 Citations
21 Claims
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1. A method for estimating the performance of an information package, comprising
receiving one or more values of respective attributes of an information package; -
obtaining, for at least one of the one or more attributes, a buzz value characterizing the level of interest in the attribute based on analysis of on-line user search activity; and providing one or more attributes and one or more buzz values as input parameters to a regression model to yield a numerical value characterizing an estimated performance of the information package, wherein the regression model is based on historical performance of a set of previous information packages relative to the one or more attributes, and provides the coefficients for the input parameters to the estimated performance of the information package. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10)
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11. An apparatus comprising
one or more network interfaces; -
a memory; one or more processors; and a performance predictor module, comprising computer-readable instructions physically stored in the memory, operable to cause the one or more processors to; receive one or more values of respective attributes of an information package; obtain, for at least one of the one or more attributes, a buzz value characterizing the level of interest in the attribute based on analysis of on-line user search activity; computing an estimated performance of the information package by applying one or more of the attributes and buzz values to a regression model, wherein the regression model is based on historical performance of a set of previous information packages relative to the one or more attributes. - View Dependent Claims (12, 13, 14, 15, 16, 17, 18, 19, 20)
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21. A method comprising
defining one or more values of respective attributes of an information package; -
obtaining, for at least one of the one or more attributes, a buzz value characterizing the level of interest in the attribute based on analysis of on-line user search activity; providing one or more attributes and one or more buzz values as input parameters to a regression model to yield an estimated click-thru rate for the information package, wherein the regression model is based on historical click-thru rate performance of a set of previous information packages relative to the one or more attributes, and provides the coefficients for the input parameters to the estimated click-thru rate for tire information package; and optimizing the information package by iteratively re-defining one or more values of the respective attributes of the information package and applying the re-defined attribute values and corresponding buzz values to the regression model until a desired estimated click-thru rate is achieved.
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Specification