Patent ID: 11961119
Assignee: SCRIBD, INC.
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 0:
1. A computer-implemented method, comprising:
generating training data based on a uniform distribution of users sampled from a user segment;
training respective machine learning models that correspond to leaves of a plurality of levels of a decision tree, each respective leaf associated with a corresponding confidence interval, the confidence interval representing an expected accuracy range of leaf output;
extracting one or more features from request data associated with a first user requesting access to user content;
feeding at least one of the features of the first user into the decision tree;
identifying, at a first level of the decision tree, a user segment relevant to the first user due to one or more of the extracted features;
identifying a relevant leaf, at a subsequent level of the decision tree below the first level, that corresponds the to the user segment relevant to the first user;
generating, at the relevant leaf, output comprising:
(a) a first prediction of receiving at least one subsequent content access request from the first user; and
(b) a second prediction of acceptance of a first type of offer by the first user in exchange for granting the subsequent content access request;

feeding the first and the second predictions to an additional leaf at a further subsequent level of the decision tree, the further subsequent level situated below the subsequent level of the relevant leaf;
generating, at the additional leaf, output comprising:
(i) a third prediction of receiving at least one content upload from the first user; and
(ii) a fourth prediction of acceptance of a second type of offer by the first user in exchange for the at least one content upload;

determining whether to provide the first user with the first type of offer or the second type of offer based on the respective output predictions and further based on the confidence intervals of the relevant leaf and the additional leaf.