Generation and Utilization of Channel Allocation Models for Resource Allocation Recommendations
AssigneeGoogle Inc.
InventorXinghua Zhao
Life of this patent
Estimating the term…
Abstract
Example embodiments of the present disclosure provide for an example method including obtaining data associated with media channels. The example method includes inputting the data into a machine learning model. The example method includes estimating, by the machine learning model, a structure of a causal graph. The example method includes applying a second machine learning model to the causal graph to estimate one or more parameters associated with the causal graph. The example method includes determining an allocation of resources to the media channels based on the causal graph.
Claims20
A computer-implemented method comprising:
- obtaining data associated with a plurality of media channels;
- inputting the data into a machine learning model;
- estimating, by the machine learning model, a structure of a causal graph;
- applying a second machine learning model to the causal graph to estimate one or more parameters associated with the causal graph;
- and
- determining an allocation of resources to the plurality of media channels based on the causal graph.
A computing system, comprising:
- one or more processors;
- and
- one or more one or more computer-readable media storing instructions that are executable to cause the one or more processors to perform operations, the operations comprising;
- obtaining data associated with a plurality of media channels;
- inputting the data into a machine learning model;
- estimating, by the machine learning model, a structure of a causal graph;
- applying a second machine learning model to the causal graph to estimate one or more parameters associated with the causal graph;
- and
- determining an allocation of resources to the plurality of media channels based on the causal graph.
One or more non-transitory computer readable media storing instructions that are executable by one or more processors to perform operations comprising:
- obtaining data associated with a plurality of media channels;
- inputting the data into a machine learning model;
- estimating, by the machine learning model, a structure of a causal graph;
- applying a second machine learning model to the causal graph to estimate one or more parameters associated with the causal graph;
- and
- determining an allocation of resources to the plurality of media channels based on the causal graph.
Dependencies are inferred from the claim text.