Predictive content placement on a managed services system

• US 10,433,010 B1
• Filed: 09/26/2017
• Issued: 10/01/2019
• Est. Priority Date: 03/04/2011
• Status: Active Grant

• Current Assignee: CSC Holdings LLC (Altice USA, Inc.)
• Original Assignee: CSC Holdings LLC (Altice USA, Inc.)
• Inventors: Neill, Richard
• Primary Examiner(s): Shang, Annan Q
• Application Number:
  US15/715,778
• Time in Patent Office: 735 Days
• Field of Search: 725 14, 725 34, 725 35, 709217-232
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/44213 Monitoring of end-user related data arrangements for monitoring the users' behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/4532 involving end-user characteristics, e.g. viewer profile, preferences monitoring of user activities for profile generation for accessing a video database G06F16/739; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02

Abstract

A distributed stochastic learning agent analyzes viewing and/or interactive service behavior patterns of users of a managed services system. The agent may operate on embedded and/or distributed devices such as set-top boxes, portable video devices, and interactive consumer electronic devices. Content may be provided with services such as video and/or interactive applications at a future time with maximum likelihood that a subscriber will be viewing a video or utilizing an interactive service at that future time. For example, user impressions can be maximized for content such as advertisements, and content may be scheduled in real-time to maximize viewership from across all video and/or interactive services.

Claims

1. A system for providing advertisements to a group of media devices from among a plurality of media devices, the system comprising:

a memory configured to store a plurality of instructions; and

a processor configured to execute the plurality of instructions, the plurality of instructions, when executed by the processor, configuring the processor to;

predict a plurality of user behaviors of a plurality of users of the plurality of media devices based upon data relating to viewing of a first advertisement from among a plurality of advertisements by the plurality of users,

select a second advertisement from among the plurality of advertisements whose content and placement coincide with user behavior for a group of users having similar user behaviors from among a plurality of user behaviors, and

provide the second advertisement to the group of media devices from among the plurality of media devices that is associated with the group of users.

2. The system of claim 1, wherein the plurality of instructions, when executed by the processor, further configure the processor to receive a plurality of state vector summaries of the data.

3. The system of claim 1, wherein the data comprises:

a plurality of user control inputs at the plurality of media devices in response to viewing the first advertisement.

4. The system of claim 3, wherein the plurality of user control inputs comprises:

channel tuning of the plurality of users;

or

commands entered by the plurality of users.

5. The system of claim 1, wherein the plurality of instructions, when executed by the processor, further configure the processor to cluster users from among the plurality of users having the similar user behaviors into the group of users.

6. The system of claim 5, wherein the plurality of instructions, when executed by the processor, configure the processor to:

cluster the users predicted to tune to a specified destination at a specified time into the group of users, and

select the second advertisement whose content and placement coincide with the specified destination at the specified time.

7. The system of claim 1, wherein the plurality of instructions, when executed by the processor, further configure the processor to select the second advertisement whose content and placement coincide with meta data from among a plurality of advertisement meta data associated with the plurality of advertisements.

8. The system of claim 7, wherein the plurality of advertisement meta data comprises:

scheduling data corresponding to the plurality of advertisements.

9. The system of claim 1, wherein the plurality of instructions, when executed by the processor, configure the processor to predict the plurality of user behaviors from the data in accordance with an algorithm.

10. The system of claim 9, wherein the algorithm comprises:

Hidden Markov Model (HMM).

11. A system for providing content to a group of media devices from among a plurality of media devices, the system comprising:

a memory configured to store a plurality of instructions; and

a processor configured to execute the plurality of instructions, the plurality of instructions, when executed by the processor, configuring the processor to;

cluster users from among a plurality of users predicted to tune to a specified destination at a specified time into a group of users from among the plurality of users in response to data relating to viewing of a first advertisement from among a plurality of advertisements by the plurality of users,

select a second advertisement from among the plurality of advertisements whose content and placement coincide with the specified destination at the specified time, and

provide the second advertisement to the group of media devices from among the plurality of media devices that is associated with the group of users.

12. The system of claim 11, wherein the plurality of instructions, when executed by the processor, further configure the processor to predict a plurality of destinations of the plurality of users and a plurality of times of the plurality of users based upon the data relating to the viewing of the first advertisement by the plurality of users.

13. The system of claim 12, wherein the data comprises:

a plurality of user control inputs at the plurality of media devices in response to viewing the first advertisement.

14. The system of claim 13, wherein the plurality of user control inputs comprises:

channel tuning of the plurality of users;

or

commands entered by the plurality of users.

15. The system of claim 11, wherein the plurality of instructions, when executed by the processor, further configure the processor to select the second advertisement whose content and placement coincide with meta data from among a plurality of meta data associated with the plurality of advertisements.

16. The system of claim 15, wherein the plurality of meta data comprises:

scheduling data corresponding to the plurality of advertisements.

17. A computer-implemented method for providing content to a group of media devices from among a plurality of media devices, the method comprising:

predicting a plurality of user behaviors of a plurality of users of the plurality of media devices based upon data relating to viewing of a first advertisement from among a plurality of advertisements by the plurality of users;

clustering users from among the plurality of users having similar user behaviors from among the plurality of user behaviors into a group of users from among the plurality of users;

selecting a second advertisement from among the plurality of advertisements whose content and placement coincide with user behavior for the group of users from among a plurality of user behaviors, and

providing the second advertisement to the group of media devices from among the plurality of media devices that is associated with the group of users.

18. The method of claim 17, further comprising:

receiving a plurality of state vector summaries of the data.

19. The method of claim 17, wherein the selecting comprises:

selecting the second advertisement whose content and placement coincide with meta data from among a plurality of meta data associated with the plurality of advertisements.

20. The method of claim 19, wherein the plurality of meta data comprises:

scheduling data corresponding to the plurality of advertisements.