SYSTEMS AND METHODS FOR NATIVE ADVERTISEMENT SELECTION AND FORMATTING

• US 20160125314A1
• Filed: 10/30/2014
• Published: 05/05/2016
• Est. Priority Date: 10/30/2014
• Status: Abandoned Application

• Current Assignee: Excalibur IP, LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Parulekar, Tejal, Mulukutla, Ramkartik, Jaladanki, Sreenivasulu
• Application Number:
  US14/528,422
• Publication Number:
  US 20160125314A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

Provided herein is a system or method for a native advertisement selection and formatting module operable to monitor displayable content and store characteristic-related information relating to the monitored content, including keyword-related information and format-related information, utilize one or more machine learning-based algorithms, analyze the characteristic-related information relating to the monitored content, including the keyword-related information and the format-related information, and based in part on the analysis, output detailed contextual settings, and select and format native advertisements to be displayed in visual association with the displayable content, based in part on the detailed contextual settings.

Claims

1. A system comprising one or more processors and a non-transitory storage medium comprising program logic for execution by the one or more processors, the program logic comprising:

a native advertisement selection and formatting module operable to;

monitor displayable content and store characteristic-related information relating to the monitored content, including keyword-related information and format-related information;

utilizing one or more machine learning-based algorithms, analyze the characteristic-related information relating to the monitored content, including the keyword-related information and the format-related information;

based in part on the analysis, output detailed contextual settings; and

select and format native advertisements to be displayed in visual association with the displayable content, based in part on the detailed contextual settings.

2. The system of claim 1, wherein selecting and formatting native advertisements further comprises selecting native advertisements based on detailed contextual settings related to keyword-related information.

3. The system of claim 1, wherein selecting and formatting native advertisements further comprises formatting native advertisements based on detailed contextual settings related to format-related information.

4. The system of claim 1, wherein detailed contextual settings include keyword-related information relating to determined frequently occurring keywords of the displayable content.

5. The system of claim 1, wherein detailed contextual settings include format-related information relating to determined frequently occurring content formatting characteristics of the displayable content.

6. The system of claim 1, wherein the displayable content includes mobile content being rendered on a content-related application.

7. The system of claim 1, wherein the native advertisement selection and formatting module is downloaded to a computerized mobile user device along with a content-related application.

8. The system of claim 1, wherein the native advertisement selection and formatting module is a remote service-based module.

9. The system of claim 1, further comprising analyzing the characteristic-related information until a threshold is reached, wherein the threshold includes at least one of a number of interactions, number of native data items analyzed, and a measure of clustering quality.

10. A method comprising:

monitoring displayable content and storing characteristic-related information relating to the monitored content, including keyword-related information and format-related information;

utilizing one or more machine learning-based algorithms, analyzing the characteristic-related information relating to the monitored content, including the keyword-related information and the format-related information;

outputting detailed contextual settings based in part on the analysis; and

selecting and formatting native advertisements to be displayed in visual association with the displayable content, based in part on the detailed contextual settings.

11. The method of claim 10, wherein selecting and formatting native advertisements further comprises selecting native advertisements based on detailed contextual settings related to keyword-related information.

12. The method of claim 10, wherein selecting and formatting native advertisements further comprises formatting native advertisements based on detailed contextual settings related to format-related information.

13. The method of claim 10, wherein detailed contextual settings include keyword-related information relating to determined frequently occurring keywords of the displayable content.

14. The method of claim 10, wherein detailed contextual settings include format-related information relating to determined frequently occurring content formatting characteristics of the displayable content.

15. The method of claim 10, wherein the displayable content includes mobile content being rendered on a content-related application.

16. The method of claim 10, wherein the native advertisement selection and formatting module is downloaded to a computerized mobile user device along with a content-related application.

17. The method of claim 10, wherein the native advertisement selection and formatting module is a remote service-based module.

18. The method of claim 10, further comprising analyzing the characteristic-related information until a threshold is reached,

19. The method of claim 18, wherein the threshold includes at least one of a number of interactions, number of native data items analyzed, and a measure of clustering quality.

20. A non-transitory computer-readable storage medium or media tangibly storing computer program logic capable of being executed by a computer processor, the program logic comprising:

a native advertisement selection and formatting engine logic operable to;

monitor displayable content and store characteristic-related information relating to the monitored content, including keyword-related information and format-related information;

utilizing one or more machine learning-based algorithms, analyze the characteristic-related information relating to the monitored content, including the keyword-related information and the format-related information, and based in part on the analysis, output detailed contextual settings; and

select and format native advertisements to be displayed in visual association with the displayable content, based in part on the detailed contextual settings.