Location-based and event-based machine learning

Patent metadata

Field	Value
Publication number	US-2025133474-A1
Application number	US-202318493463-A
Country	US
Kind code	A1
Filing date	Oct 24, 2023
Priority date	Oct 24, 2023
Publication date	Apr 24, 2025
Grant date	—

Abstract

In some implementations, a machine learning system may generate a predicted event level, associated with an entity, based on event information associated with the entity. The machine learning system may determine that the predicted event level satisfies a threshold. The machine learning system may select, in response to determining that the predicted event level satisfies the threshold, a set of users. The machine learning system may transmit at least one communication to one or more user devices associated with the set of users.

First claim

What is claimed is:

1 . A system for location-based and event-based machine learning, the system comprising:
one or more memories; and one or more processors, communicatively coupled to the one or more memories, configured to:
generate a predicted event level, associated with an entity, based on event information associated with the entity;
determine that the predicted event level satisfies a threshold;
receive a set of location indications associated with a set of users;
provide the set of location indications to a machine learning model, in response to determining that the predicted event level satisfies the threshold, in order to receive an indication, from the machine learning model, of a subset of users in the set of users; and
transmit at least one communication to one or more user devices associated with the subset of users.

2 . The system of claim 1 , wherein the event information is associated with a first time period, and the predicted event level is associated with a second time period subsequent to the first time period.

3 . The system of claim 1 , wherein the one or more processors are configured to:
receive additional event information associated with the set of users, wherein the additional event information is provided to the machine learning model in order to receive the indication of the subset of users.

4 . The system of claim 1 , wherein the one or more processors, to generate the predicted event level, are configured to:
provide the event information, associated with the entity, to an additional machine learning model in order to receive the predicted event level from the additional machine learning model.

5 . The system of claim 4 , wherein the additional machine learning model is unique to the entity.

6 . The system of claim 1 , wherein the one or more processors are configured to:
transmit, to an administrator device, an indication of the subset of users.

7 . The system of claim 1 , wherein the one or more processors are configured to:
transmit, to an administrator device, an indication of an amount associated with transmitting the at least one communication.

8 . A method of event-based machine learning, comprising:
generating, by a machine learning system, a predicted event level, associated with an entity, based on event information associated with the entity; determining, by the machine learning system, that the predicted event level satisfies a threshold; selecting, by the machine learning system and in response to determining that the predicted event level satisfies the threshold, a set of users; and transmitting at least one communication to one or more user devices associated with the set of users.

9 . The method of claim 8 , further comprising:
receiving, from an administrator device, an indication of the threshold.

10 . The method of claim 8 , further comprising:
receiving, from an administrator device, at least a portion of the at least one communication.

11 . The method of claim 8 , further comprising:
receiving, from an administrator device, an indication of a condition, wherein the set of users are selected using the condition.

12 . The method of claim 8 , further comprising:
generating, by the machine learning system, an additional predicted event level, associated with an additional entity, based on additional event information associated with the additional entity; determining, by the machine learning system, that the additional predicted event level fails to satisfy an additional threshold; and refraining from selecting an additional set of users in response to determining that the additional predicted event level fails to satisfy the additional threshold.

13 . The method of claim 8 , further comprising:
determining, by the machine learning system, that a weighted distance associated with the entity and the set of users is greater than an additional weighted distance associated with an additional entity and the set of users, wherein the set of users is selected based on the weighted distance being greater than the additional weighted distance.

14 . The method of claim 8 , further comprising:
receiving a set of location indications associated with the set of users, wherein the set of users is selected based on the set of location indications.

15 . A non-transitory computer-readable medium storing a set of instructions for configuring event-based machine learning, the set of instructions comprising:
one or more instructions that, when executed by one or more processors of a device, cause the device to:
transmit, to a remote system, a registration message that authorizes a remote system to access event information;
transmit, to the remote system, an indication of a threshold;
transmit, to the remote system, a data structure encoding at least one communication; and
receive, from the remote system, a confirmation that the at least one communication was sent to a set of users in response to a predicted event level satisfying the threshold.

16 . The non-transitory computer-readable medium of claim 15 , wherein the registration message includes a set of credentials associated with the event information.

17 . The non-transitory computer-readable medium of claim 15 , wherein the indication of the threshold includes a selection of a value for the threshold from a plurality of candidate values.

18 . The non-transitory computer-readable medium of claim 15 , wherein the confirmation indicates a quantity of users in the set of users.

19 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, when executed by the one or more processors, cause the device to:
receive, from the remote system, an indication of an amount associated with transmission of the at least one communication.

20 . The non-transitory computer-readable medium of claim 15 , wherein the one or more instructions, when executed by the one or more processors, cause the device to:
transmit, to the remote system, an indication of a geographic area, wherein the confirmation is received based on the set of users being associated with the geographic area.

Assignees

• Capital One Services Llc

Inventors

• Reinert Owen
• Goodsitt Jeremy
• Turner Taylor
• Au-Yeung Justin

Classifications

• H04W92/08

  between user and terminal device · CPC title

• H04W40/18 Primary

  based on predicted events · CPC title

• H04W4/02

  Services making use of location information · CPC title

• G06N20/00 Primary

  Machine learning · CPC title