US 2022/0277227 A1 · PREDICTING OCCURRENCES OF TARGETED CLASSES OF EVENTS USING TRAINED ARTIFICIAL-INTELLIGENCE PROCESSES

Abstract

The disclosed embodiments include computer-implemented apparatuses and processes that dynamically predict future occurrences of targeted classes of events using adaptively trained machine-learning or artificial-intelligence processes. For example, an apparatus may generate an input dataset based on interaction data associated with a prior temporal interval, and may apply a trained, gradient-boosted, decision-tree process to the input dataset. Based on the application of the trained, gradient-boosted, decision-tree process to the input dataset, the apparatus may generate output data representative of an expected occurrence of a corresponding one of a plurality of targeted events during a future temporal interval, which may be separated from the prior temporal interval by a corresponding buffer interval. The apparatus may also transmit a portion of the generated output data to a computing system, and the computing system may transmit digital content to a device associated with the expected occurrence based on the portion of the output data.

Claims20

Dependent claims

An apparatus, comprising:

a memory storing instructions;
a communications interface;
and
at least one processor coupled to the memory and the communications interface, the at least one processor being configured to execute the instructions to:
generate an input dataset based on elements of first interaction data associated with a first temporal interval;
based on an application of a trained artificial intelligence process to the input dataset, generate output data indicative of an expected occurrence of a corresponding one of a plurality of targeted events during a second temporal interval, the second temporal interval being subsequent to the first temporal interval and being separated from the first temporal interval by a corresponding buffer interval;
and
transmit at least a portion of the output data to a computing system via the communications interface, the computing system being configured to transmit digital content to a device associated with the expected occurrence based on the portion of the output data.

5 more elements

A computer-implemented method, comprising:

generating, using at least one processor, an input dataset based on elements of first interaction data associated with a first temporal interval;
based on an application of a trained artificial intelligence process to the input dataset, generating, using the at least one processor, output data indicative of an expected occurrence of a corresponding one of a plurality of targeted events during a second temporal interval, the second temporal interval being subsequent to the first temporal interval and being separated from the first temporal interval by a corresponding buffer interval;
and
transmitting, using the at least one processor, at least a portion of the output data to a computing system, the computing system being configured to transmit digital content to a device associated with the expected occurrence based on the portion of the output data.

1 more element

Dependencies are inferred from the claim text.

Predicting occurrences of targeted classes of events using trained artificial-intelligence processes

Life of this patent

Predicting occurrences of targeted classes of events using trained artificial-intelligence processes

Life of this patent

Abstract

Claims20