US 2019/0156231 A1Published application

User segmentation using predictive model interpretation

AssigneeAdobe Systems Incorporated

InventorsPiyush Gupta, Nikaash Puri

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Abstract

Systems and methods are disclosed herein for determining user segments created by a predictive model based on user behavioral data. A data analysis application executing on a computing device receives training data and a user input defining an outcome of interest. The data analysis application trains a predictive model with the training data and the outcome of interest. The data analysis application generates input data for each of a set of conditions determined from the training data. The data analysis application receives predicted outcome from the predictive model based on the input data. The data analysis application determines the relevance of the condition based on a comparison of the predicted outcome and the outcome of interest. The data analysis application generates a user segment that comprises a condition from the set of conditions based on the relevance of the condition.

Claims20

Dependent claims

A computer -implemented method for determining user segments created by a predictive model based on user behavioral data, the method comprising:

receiving, by a computing device, training data and user input, the training data associated with training a predictive model and comprising a plurality of instances, each instance associated with a user interaction within a computer network and comprising a plurality of attributes and an outcome associated with the user interaction, and an operator input defining an outcome of interest;
generating, by the computing device, a set of conditions from the training data, each condition comprising an attribute and a range of values for the attribute;
determining, by the computing device, a set of relevant conditions to the predictive model from the set of conditions to the outcome of interest, a relevance of each condition determined by at least:
generating, from the training data, input data that comprises the attribute of the condition,
receiving a predicted outcome from the predictive model based on the input data, and
determining the relevance of the condition based on a comparison of the predicted outcome and the outcome of interest;
generating, by the computing device, a user segment that comprises a condition from the set of relevant conditions based on the relevance of the condition;
and
presenting, by the computing device, the user segment to the operator at an interface.

6 more elements

A system comprising:

a computer-readable medium storing non-transitory computer-executable program instructions for determining user segments created by a predictive model based on user behavioral data;
and
a processing device communicatively coupled to the computer-readable medium for executing the non-transitory computer-executable program instructions, wherein executing the non-transitory computer-executable program instructions configures the processing device to perform operations comprising:
receiving, by a computing device, training data and user input, the training data associated with training a predictive model and comprising a plurality of instances, each instance associated with a user interaction within a computer network and comprising a plurality of attributes and an outcome associated with the user interaction, and an operator input defining an outcome of interest;
generating, by the computing device, a set of conditions from the training data, each condition comprising an attribute and a range of values for the attribute;
determining, by the computing device, a set of relevant conditions to the predictive model from the set of conditions to the outcome of interest, a relevance of each condition determined by at least:
generating, from the training data, input data that comprises the attribute,
receiving a predicted outcome from the predictive model based on the input data, and
determining the relevance of the condition based on a comparison of the predicted outcome and the outcome of interest;
generating, by the computing device, a user segment that comprises a condition from the set of relevant conditions based on the relevance of the condition;
and
presenting, by the computing device, the user segment to the operator at an interface.

9 more elements

A computer-readable storage medium storing non-transitory computer-executable program instructions, wherein when executed by a processing device, the program instructions cause the processing device to perform operations comprising:

receiving, by a computing device, training data and user input, the training data associated with training a predictive model and comprising a plurality of instances, each instance associated with a user interaction within a computer network and comprising a plurality of attributes and an outcome associated with the user interaction, and an operator input defining an outcome of interest;
generating, by the computing device, a set of conditions from the training data, each condition comprising an attribute and a range of values for the attribute;
determining, by the computing device, a set of relevant conditions to the predictive model from the set of conditions to the outcome of interest, a relevance of each condition determined by at least:
generating, from the training data, input data that comprises the attribute,
receiving a predicted outcome from the predictive model based on the input data, and
determining the relevance of the condition based on a comparison of the predicted outcome and the outcome of interest;
generating, by the computing device, a user segment that comprises a condition from the set of relevant conditions based on the relevance of the condition;
and
presenting, by the computing device, the user segment to the operator at an interface.

6 more elements

Dependencies are inferred from the claim text.