Method and system for providing 'what's next' data

• US 20100094866A1
• Filed: 01/29/2008
• Published: 04/15/2010
• Est. Priority Date: 01/29/2007
• Status: Active Grant

• Current Assignee: Home Box Office Incorporated (Warner Bros. Discovery, Inc.)
• Original Assignee: Home Box Office Incorporated (Warner Bros. Discovery, Inc.)
• Inventors: Beyler, John Clayton, Grishaver, Alexander Thompson, Dibartolomeo, Jeffrey A., Stalling, Lars, Probst, Bruce, Gabriel, Michael, Parviainen, Juho, Cuttner, Craig D.
• Granted Patent: US 9,477,666 B2
• Time in Patent Office: Days
• US Class Current: 707/723
• CPC Class Codes: G06F 16/437 Administration of user profiles, e.g. generation, initialisation, adaptation, distribution
• CPC Class Codes: G06F 16/735 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/78 Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/44224 Monitoring of user activity on external systems, e.g. Internet browsing
• 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 21/4826 using recommendation lists, e.g. of programs or channels sorted out according to their score
• CPC Class Codes: H04N 7/163 by receiver means only

Abstract

A system and method for generating a list of content is disclosed. A processor may store in memory at least one content preference of a user, may store at least one non-user content preference of at least one entity other than the user, may associate the at least one non-user content preference with the user, and may generate the content list based on a combination of the at least one content preference of the user and the at least one non-user content preference for output to the user.

Claims

1. A data generation method, comprising:

storing at least one content preference of a first user;

storing at least one non-user content preference, which is at least one content preference of at least one entity other than the first user;

associating the at least one non-user content preference with the first user; and

generating a content list based on a combination of the stored at least one content preference of the user and the stored at least one non-user content preference for output to the first user.

2. The data generation method of claim 1, wherein the generating the content list comprises:

in a first comparing step, comparing content metadata of a plurality of content to the at least one content preference of the first user;

at least one of selecting from and sorting the plurality of content based on the first comparing step to generate a first list;

in a second comparing step, for one or more of the at least one entity, comparing the content metadata to the at least one non-user content preference;

for each of the at least one entity to the at least one non-user content preference of which the content metadata is compared in the second comparing step, at least one of selecting from and sorting the plurality of content based on the comparison to the at least one non-user content preference to generate a second list; and

modifying the first list based on each of the second lists.

3. The data generation method of claim 2, wherein (a) the first comparing step and the at least one of selecting from and sorting based on the first comparing step and (b) the second comparing step and the at least one of selecting from and sorting based on the second comparing step are performed in parallel.

4. The data generation method of claim 2, further comprising:

for one or more of the at least one entity, applying a weight to the at least one non-user preference of the entity;

wherein a degree to which the first list is modified based on a second list generated based on the at least one non-user content preference of a particular entity to which a particular weight is applied depends on the particular weight.

5. The data generation method of claim 4, wherein the applied weights are one of weighting input set by the first user, predefined, set by a content provider, automatically set based on a log of content selections, and based on a combination of the weighting input set by the user and the log of content selections.

6. The data generation method of claim 4, further comprising:

comparing the weighting input set by the first user to weighting input of other users;

for the generating the content list, using at least one content preference of users who have input weighting input determined in the comparing step to be similar to the weighting input set by the first user.

7. The data generation method of claim 4, further comprising:

recording a log of inputs indicating weights received over time;

recognizing a pattern in a change in the weights; and

automatically changing weights applied to at least one of each of the at least one entity and the at least one content preference of the first user in accordance with the recognized pattern.

8. The data generation method of claim 1, wherein the at least one entity includes at least one of a particular demographic, one or more second users, and one or more content providers.

9. The data generation method of claim 8, wherein the one or more second users includes a plurality of selected critics, the method further comprising:

applying different weights to non-user preferences of different ones of the critics.

10. The data generation method of claim 1, wherein the at least one entity includes:

(a) one or more users determined to be related to the first user in a predetermined way; and

(b) at least one of (i) one or more users selected by the first user and (ii) a content provider.

11. The data generation method of claim 10, wherein the generating the content list comprises:

modifying the at least one content preference of the first user;

comparing content metadata of a plurality of content to the modified at least one preference;

at least one of selecting from and sorting the plurality of content based on the comparing; and

arranging the at least one of selected and sorted content in a list.

12. The data generation method of claim 10, wherein the generating the content list comprises:

in a first comparing step, comparing content metadata of a plurality of content to the at least one content preference of the first user;

at least one of selecting from and sorting the plurality of content based on the first comparing step to generate a first list;

in a second comparing step, for each of (a) and (b), comparing the content metadata of the plurality of content to the at least one non-user content preference;

for each of (a) and (b), at least one of selecting from and sorting the plurality of content based on the comparison to the at least one non-user content preference to generate a corresponding second list; and

modifying the first list based on each of the second lists.

13. The data generation method of claim 1, wherein one or more of the at least one entity is selected as a reference by the first user.

14. The data generation method of claim 1, wherein the at least one content preference of the first user includes at least one of at least one preference specified by the first user, an observed preference, a preference determined based on a mood of the first user, and a counter-programming preference indicating a preference to steer away from a program type.

15. The data generation method of claim 14, wherein the observed preference is determined based on at least one of past content selections by the first user and at least one currently selected content.

16. The data generation method of claim 14, further comprising:

detecting the'"'"'mood by;

storing a log of user selections;

based on the log, recognizing a selections pattern; and

matching the pattern to the mood.

17. The data generation method of claim 1, further comprising:

for display of the content list, overlaying the content list on ending credits of a program.

18. The data generation method of claim 1, further comprising:

displaying the content list in an intermission screen provided when a program is paused.

19. The data generation method of claim 1, further comprising:

displaying the content list in a display; and

in response to a change in any of the at least one content preference of the user and the at least one non-user content preference occurring while the content list is displayed;

generating a new content list; and

modifying the display in accordance with the new content list even if the displayed content list is not exited.

20. The data generation method of claim 1, further comprising:

for content listed in the content list that is available for playback on demand, generating a virtual linear playback channel including the content, wherein the virtual linear playback channel linearly plays back the content when the channel is active.

25. The data generation method of claim 1, wherein the content list is a list of programs receivable at a set-top box and selectable for viewing on a display device.

21. A method for selecting content, comprising:

inputting at least one content preference of a user; and

receiving a content list generated based on a combination of the at least one content preference and at least one non user content preference of at least one entity other than the first user.

26. The data generation method of claim 21, wherein the content list is a list of programs receivable at a set-top box and selectable for viewing on a display device.

22. A data generation method, comprising:

storing a user profile that indicates at least one content preference of a user;

receiving a list of promoted content;

receiving from each of at least one media source a list of available content; and

in accordance with a combination of the user profile and the list of promoted content, generating a content list that includes parts of the at least one list of available content.

23. A data generation method, comprising:

recording a log of user inputs received over time indicating weights to be applied to different ones of a plurality of sets of content preferences, the different ones of the plurality of sets including content preferences of different entities;

recognizing a pattern in the log of a change in the weights;

in accordance with the recognized pattern, automatically changing weights applied to the different ones of the plurality of sets; and

generating a content list based on a combination of the plurality of sets, an extent of contribution to the list by the different ones of the plurality of sets depending on the weights applied to the sets.

24. A data generation method, comprising:

in a first comparing step, comparing, by a first search engine, content metadata of a plurality of content to at least one content preference of a first user;

selecting from the plurality of content based on the first comparing step to generate a first list;

in a second comparing step, comparing, by a second search engine, the content metadata to at least one content preference of one or more users determined to be related to the first user in a predetermined way;

selecting from the plurality of content based on the second comparing step to generate a second list;

in a third comparing step, comparing, by a third search engine, the content metadata to at least one content preference of at least one of (a) one or more users selected by the first user and (b) a content provider;

selecting from the plurality of content based on the third comparing step to generate a third list; and

generating a content list based on a combination of the first, second, and third lists.