Content ranking and serving on a multi-user device or interface

• US 9,633,368 B2
• Filed: 05/25/2012
• Issued: 04/25/2017
• Est. Priority Date: 05/25/2012
• Status: Active Grant

• Current Assignee: Apple Inc.
• Original Assignee: Apple Inc.
• Inventors: Greenzeiger, Michael Froimowitz, Sanghavi, Mehul K., Phulari, Ravindra
• Primary Examiner(s): Hudspeth, David
• Assistant Examiner(s): Nguyen, Timothy
• Application Number:
  US13/480,724
• Publication Number:
  US 20130317828A1
• Time in Patent Office: 1,796 Days
• Field of Search: 704275
• CPC Class Codes: G06F 16/00 Information retrieval; Database structures therefor; File system structures therefor
• CPC Class Codes: G06F 3/0482 Interaction with lists of selectable items, e.g. menus
• CPC Class Codes: G06Q 30/0251 Targeted advertisements
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute

Abstract

The effectiveness of targeted content delivery at a multi-user interface can be directly linked to a proper targeting of users. A way of improving targeted content delivery at a multi-user interface can be to determine which users should be targeted based on one or more criteria. The present technology provides various methodologies for selecting one or more users associated with a multi-user interface to receive targeted content. Such users can be selected based on criteria associated with a ranking or priority of the users, criteria associated with an analysis of their interactions with the multi-user interface, criteria based on their most common characteristics, or any combination thereof. The user characteristics associated with such identified used can then be utilized to determine which content should be delivered to the multi-user interface.

Claims

1. A method comprising:

detecting, by a processor, user interactions from at least a first user and a second user concurrently engaged with a first client device;

in response to detecting the user interactions, obtaining, by the processor, user characteristics for the first user and the second user;

determining, by the processor, an age of the first user and an age of the second user based on the user characteristics of the first user and the second user;

determining, based on the age of the first user and the age of the second user, that the first user is older than the second user;

in response to determining that the first user is older than the second user, identifying, by the processor, the first user for targeting; and

selecting, by the processor, content for the first client device, the content being specifically selected for the first user based on at least one of the user characteristics associated with the first user.

2. The method of claim 1, wherein the obtaining further comprises:

receiving registration information for the first user and the second user; and

accessing stored user data to retrieve the user characteristics for the first user and the second user.

3. The method of claim 1, wherein the obtaining further comprises:

associating a portion of user interactions at the first client device to the first user, wherein the portion of user interactions are detected while the first user and the second user are concurrently engaged with the first client device; and

generating the user characteristics for the first user based at least on the portion of the user interactions.

4. The method of claim 3, wherein the portion of user interactions comprises at least one of an audio interaction or gestural interaction.

5. The method of claim 1, wherein the user interactions comprise voice interactions, the method further comprising:

inferring user characteristics associated with the first user and the second user based on the voice interactions, the user characteristics being inferred based on a feature of at least one of a voice or a content of speech associated with the voice interactions, wherein the first user is identified based the user characteristics inferred.

6. A system comprising:

one or more computer processors; and

a memory storing instructions that, when executed by the one or more computer processors, cause the system to;

detect user interactions from at least a first user and a second user concurrently engaged with a first client device;

in response to detecting the user interactions, obtain user characteristics for the first user and the second user;

determine an age of the first user and an age of the second user based on the user characteristics of the first user and the second user;

determine, based on the age of the first user and the age of the second user, that the first user is older than the second user;

in response to determining that the first user is older than the second user, identify the first user for targeting; and

select content for the first client device, the content being specifically selected for the first user based on at least one of the user characteristics associated with the first user.

7. The system of claim 6, wherein the obtaining further comprises:

receiving registration information for the first user and the second user; and

accessing stored user data to retrieve the user characteristics for the first user and the second user.

8. The system of claim 6, wherein the obtaining further comprises:

associating a portion of user interactions at the first client device to the first user, wherein the portion of user interactions are detected while the first user and the second user are concurrently engaged with the first client device; and

generating the user characteristics for the first user based at least on the portion of the user interactions.

9. The system of claim 8, wherein the portion of user interactions comprises at least one of an audio interaction or gestural interaction.

10. The system of claim 6, wherein the user interactions comprise voice interactions, the instructions further causing the system to:

infer user characteristics associated with the first user and the second user based on the voice interactions, the user characteristics being inferred based on a feature of at least one of a voice or a content of speech associated with the voice interactions, wherein the first user is identified based the user characteristics inferred.

11. A non-transitory computer-readable medium storing instructions that, when executed by a computing device, cause the computing device to:

detect user interactions from at least a first user and a second user concurrently engaged with a first client device;

in response to detecting the user interactions, obtain user characteristics for the first user and the second user;

determine an age of the first user and an age of the second user based on the user characteristics of the first user and the second user;

determine, based on the age of the first user and the age of the second user, that the first user is older than the second user;

in response to determining that the first user is older than the second user, identify the first user for targeting; and

select content for the first client device, the content being specifically selected for the first user based on at least one of the user characteristics associated with the first user.

12. The non-transitory computer-readable medium of claim 11, wherein the obtaining further comprises:

receiving registration information for the first user and the second user; and

accessing stored user data to retrieve the user characteristics for the first user and the second user.

13. The non-transitory computer-readable medium of claim 11, wherein the obtaining further comprises:

associating a portion of user interactions at the first client device to the first user, wherein the portion of user interactions are detected while the first user and the second user are concurrently engaged with the first client device; and

generating the user characteristics for the first user based at least on the portion of the user interactions.

14. The non-transitory computer-readable medium of claim 13, wherein the portion of user interactions comprises at least one of an audio interaction or gestural interaction.

15. The non-transitory computer-readable medium of claim 11, wherein the user interactions comprise voice interactions, the instructions further causing the computing device to:

infer user characteristics associated with the first user and the second user based on the voice interactions, the user characteristics being inferred based on a feature of at least one of a voice or a content of speech associated with the voice interactions, wherein the first user is identified based the user characteristics inferred.