Delivering advertisements based on user sentiment and learned behavior

Patent metadata

Field	Value
Publication number	US-11017430-B2
Application number	US-201816193206-A
Country	US
Kind code	B2
Filing date	Nov 16, 2018
Priority date	Nov 16, 2018
Publication date	May 25, 2021
Grant date	May 25, 2021

Abstract

Provided are embodiments including a method, system, and computer program product for identifying how to deliver advertisements to a user based on the user sentiment and learned behavior. The embodiments provide for collecting information on the sentiment of a user, monitoring user interactions based at least in part on the collected emotional information on the sentiment of the user, and determining a pattern of user interactions with one or more applications of a user device based on the sentiment information. The embodiments also provide for determining a pattern of user responses to an advertisement based on the sentiment information, and generating a profile based at least in part on the pattern of user interactions and the pattern of user responses.

First claim

What is claimed is:

1. A computer-implemented method for identifying how to push advertisements based on emotion and learned behavior, the computer-implemented method comprising:
collecting emotional information of a user;
monitoring user interactions based at least in part on the collected emotional information of the user;
determining a pattern of user interactions with one or more applications of a user device based on the emotional information, wherein determining the pattern of user interactions comprises determining, within the one or more applications, if the user interacts with a pop-up advertisement, a link to an advertisement, a video advertisement, and an advertisement provided in a banner of a webpage;
determining a pattern of user responses to an advertisement based on the emotional information;
generating a profile based at least in part on the pattern of user interactions and the pattern of user responses;
detecting an emotional state of the user;
selecting the advertisement and the interaction within one or more applications based at least in part on the emotional state of the user and the profile;
responsive to selecting the advertisement, determining a channel to transmit the selected advertisement, wherein the channel identifies one or more types of applications and one or more types of user devices, wherein the channel is determined based on a success; and
transmitting the selected advertisement to the user device through the determined channel based at least in part on the success and displaying, on a display, the selected advertisement in the determined interaction within one or more applications on the user device.

2. The computer-implemented method of claim 1 , further comprising classifying the pattern of user interactions and the pattern of user responses based at least in part on an emotional state of the user.

3. The computer-implemented method of claim 1 , wherein determining the pattern of user interactions comprises using social network applications, a messaging application, a gaming application, a retail website, or a search engine.

4. The computer-implemented method of claim 1 , wherein determining the pattern of user responses comprises determining whether an advertisement has resulted in a retail purchase related to the advertisement.

5. The computer-implemented method of claim 1 , further comprising selecting advertisements based on one or more advertisement service levels, wherein each of the one or more advertisement service levels indicates a probability the selected advertisements result in a purchase.

6. A system for identifying how to push advertisements based on emotion and learned behavior, the system comprising:
a storage medium, the storage medium being coupled to a processor;
the processor configured to:
collect emotional information of a user;
monitor user interactions based at least in part on the collected emotional information of the user;
determine a pattern of user interactions with one or more applications of a user device based on the emotional information;
determine a pattern of user responses to advertisements based on the emotional information, wherein determining the pattern of user interactions comprises determining, within the one or more applications, if the user interacts with a pop-up advertisement, a link to an advertisement, a video advertisement, and an advertisement provided in a banner of a webpage;
generate a profile based at least in part on the pattern of user interactions and the pattern of user responses;
detect an emotional state of the user;
select the advertisement and the interaction within one or more applications based at least in part on the emotional state of the user and the profile;
responsive to selecting the advertisement, determine a channel to transmit the selected advertisement, wherein the channel identifies one or more types of applications and one or more types of user devices, wherein the channel is determined based on a success; and
transmit the selected advertisement to the user device through the determined channel based at least in part on the success and display the selected advertisement in the determined interaction within one or more applications on the user device.

7. The system of claim 6 , wherein the processor is further configured to classify the pattern of user interactions and the pattern of user responses based at least in part on an emotional state of the user.

8. The system of claim 6 , wherein determining the pattern of user interactions comprises using social network applications, a messaging application, a gaming application, a retail website, or a search engine.

9. The system of claim 6 , wherein determining the pattern of user responses comprises determining whether an advertisement has resulted in a retail purchase related to the advertisement.

10. The system of claim 6 , further comprising determining a channel to transmit the selected advertisement, wherein the channel identifies one or more types of applications and one or more types of user devices.

11. A non-transitory computer program product for identifying how to push advertisements based on emotion and learned behavior, the computer program product comprising a computer-readable storage medium having program instructions embodied therewith, the program instructions executable by a processor to cause the processor to:
collect emotional information of a user;
monitor user interactions based at least in part on the collected emotional information of the user;
determine a pattern of user interactions with one or more applications of a user device based on the emotional information, wherein determining the pattern of user interactions comprises determining, within the one or more applications, if the user interacts with a pop-up advertisement, a link to an advertisement, a video advertisement, and an advertisement provided in a banner of a webpage;
determine a pattern of user responses to advertisements based on the emotional information;
generate a profile based at least in part on the pattern of user interactions and the pattern of user responses;
detect an emotional state of the user;
select the advertisement and the interaction within one or more applications based at least in part on the emotional state of the user and the profile;
responsive to selecting the advertisement, determine a channel to transmit the selected advertisement, wherein the channel identifies one or more types of applications and one or more types of user devices, wherein the channel is determined based on a success; and
transmit the selected advertisement to the user device through the determined channel based at least in part on the success and display the selected advertisement in the determined interaction within one or more applications on the user device.

12. The computer program product of claim 11 , wherein the instructions are further executable by the processor to cause the processor to classify the pattern of user interactions and the pattern of user responses based at least in part on an emotional state of the user.

13. The computer program product of claim 11 , wherein determining the pattern of user interactions is based on at least one of a social network applications, a messaging application, a gaming application, a retail website, or a search engine.

14. The computer program product of claim 11 , wherein determining the pattern of user responses comprises determining whether an advertisement has resulted in a retail purchase related to the advertisement.

15. The computer program product of claim 11 , wherein the instructions a

Assignees

• IBM

Inventors

• Chan Yuk L
• Lagares-Greenblatt Heidi
• Li Jenny S
• Naphade Deepti M
• Wang Xinlin

Classifications

• G06Q30/0255 Primary

  based on user history · CPC title

• G06Q30/0271 Primary

  Personalized advertisement · CPC title