US 2026/0089050 A1 · UTILIZING MACHINE LEARNING MODELS TO GENERATE PREDICTED REFEREE INTERACTION METRICS FOR GENERATING AND TRANSMITTING DIGITAL NOTIFICATIONS ACROSS COMPUTER NETWORKS TO REFERRER CLIENT DEVICES

Abstract

The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing machine learning to generate predicted referee interaction metrics for building a digital notification distribution policy for tiers of referrer client devices and transmitting digital notifications to referrer client devices across computer networks. In particular, in one or more embodiments, the disclosed systems utilize a referee interaction prediction machine learning model that generate predicted referee interaction metrics indicating likelihoods of downstream interactions of referee client devices based on features of referrer client devices. The disclosed systems generate referrer client device tiers for referrer client devices based on the predicted referee interaction metrics and then utilizes an optimization model to generate a digital notification distribution policy for the tiers of the referrer client devices. Further, the disclosed systems transmit digital notifications to referrer client devices in accordance with the digital notification policy and the referrer client device tiers.

Claims20

Dependent claims

A computer-implemented method comprising:

generating, utilizing a trained referee interaction prediction machine learning model, a plurality of predicted referee interaction metrics from a plurality of referrer client device features;
generating a plurality of referrer client device tiers based on the plurality of predicted referee interaction metrics;
generating, utilizing an optimization model, a digital notification distribution policy for the plurality of referrer client device tiers from a set of measured referee client device interactions for the plurality of referrer client device tiers and a target interaction metric;
and
transmitting digital notifications to referrer client devices in accordance with the digital notification distribution policy and the plurality of referrer client device tiers.

2 more elements

A non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause a computer system to:

generate, utilizing a trained referee interaction prediction machine learning model, a plurality of predicted referee interaction metrics from a plurality of referrer client device features;
generate a plurality of referrer client device tiers based on the plurality of predicted referee interaction metrics;
generate, utilizing an optimization model, a digital notification distribution policy for the plurality of referrer client device tiers from a set of measured referee client device interactions for the plurality of referrer client device tiers and a target interaction metric;
and
transmit digital notifications to referrer client devices in accordance with the digital notification distribution policy and the plurality of referrer client device tiers.

2 more elements

A system comprising:

at least one processor;
and
at least one non-transitory computer-readable storage medium storing instructions that, when executed by the at least one processor, cause the system to:
generate, utilizing a trained referee interaction prediction machine learning model, a plurality of predicted referee interaction metrics from a plurality of referrer client device features;
generate a plurality of referrer client device tiers based on the plurality of predicted referee interaction metrics;
generate, utilizing an optimization model, a digital notification distribution policy for the plurality of referrer client device tiers from a set of measured referee client device interactions for the plurality of referrer client device tiers and a target interaction metric;
and
transmit digital notifications to referrer client devices in accordance with the digital notification distribution policy and the plurality of referrer client device tiers.

5 more elements

Dependencies are inferred from the claim text.

Utilizing machine learning models to generate predicted referee interaction metrics for generating and transmitting digital notifications across computer networks to referrer client devices

Life of this patent

Utilizing machine learning models to generate predicted referee interaction metrics for generating and transmitting digital notifications across computer networks to referrer client devices

Life of this patent

Abstract

Claims20