Patent ID: 11907962
Assignee: PINTEREST, INC.
Field: IT methods for management (Electrical engineering)
Classification: CPC G | IPC G

Claim 6:
7. A computer-readable medium bearing computer-executable instructions that, when executed by an online service operating on a computing system comprising at least a processor executing the instructions, carries out a method comprising:
generating a training dataset;
segmenting the training dataset into a plurality of batches of training data;
training a machine learning model using the plurality of batches of training data to generate a trained machine learning model configured to predict conversion counts and error rates based on input online behaviors, wherein training the machine learning model includes:
training, using the plurality of batches of training data, the machine learning model by iteratively randomly disabling a processing node of the machine learning model, training the machine learning model with a respective batch of training data of the plurality of batches of training data while the processing node is disabled, and re-enabling the processing node;

capturing online behaviors of a plurality of subscribers in response to content;
for each of the plurality of subscribers, determining whether the subscriber is a measurable subscriber or a non-measurable subscriber, wherein a measurable subscriber is a subscriber whose online behaviors are accessible and can be evaluated;
for each measurable subscriber:
determining a first conversion count in response to the content; and
adding the first conversion count to a total conversion count for the content;

for each non-measurable subscriber:
processing the captured online behaviors of the non-measurable subscriber to determine, using the trained machine learning model, a second conversion count and an estimated error rate of the second conversion count in response to the content, wherein the trained machine learning model is trained to compute conversion counts and corresponding estimated error rates for measurable subscribers based at least in part on the captured online behavior of the subscribers; and
adding the second conversion count to the total conversion count upon a determination that the estimated error rate falls below a threshold; and

storing the total conversion count.