Recommending media programs based on media program popularity

• US 9,769,528 B2
• Filed: 06/16/2015
• Issued: 09/19/2017
• Est. Priority Date: 08/24/2007
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Jeon, Joon-Hee, Dureau, Vincent, Benting, Steve D., Lin, Zhenhai, Miller, Michael W., Patel, Manish G.
• Primary Examiner(s): LE, UYEN T
• Application Number:
  US14/740,698
• Publication Number:
  US 20150281785A1
• Time in Patent Office: 826 Days
• Field of Search: None
• CPC Class Codes: G06F 16/40 of multimedia data, e.g. slideshows comprising image and additional audio data retrieval of still image data G06F16/50; retrieval of audio data G06F16/60; retrieval of video data G06F16/70
• CPC Class Codes: G06F 16/74 Browsing; Visualisation therefor end-user interfaces for requesting or interacting with video content, e.g. video on demand interfaces or electronic program guides, H04N21/472
• CPC Class Codes: H04N 21/251 Learning process for intelligent management, e.g. learning user preferences for recommending movies details of learning user preferences for the retrieval of video data in a video database G06F16/739; computer systems using learning methods G06N3/08
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• CPC Class Codes: H04N 21/254 Management at additional data server, e.g. shopping server, rights management server arrangements for maintenance or administration in data networks H04L41/00; network services using third party service providers H04L67/53
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; 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 21/431 Generation of visual interfaces for content selection or interaction; Content or additional data rendering
• CPC Class Codes: H04N 21/44226 on social networks
• 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 21/4667 Processing of monitored end-user data, e.g. trend analysis based on the log file of viewer selections
• CPC Class Codes: H04N 21/4668 for recommending content, e.g. movies
• CPC Class Codes: H04N 21/47 End-user applications
• CPC Class Codes: H04N 21/4756 for rating content, e.g. scoring a recommended movie
• 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 21/4828 for searching program descriptors retrieval of video data G06F16/739

Abstract

A computer-implemented method includes receiving information expressing a user'"'"'s interest in one or more media programs, obtaining information indicative of popularity for a plurality of media programs responsive to the received information by individuals other than the user, and transmitting one or more recommendations of media programs for display to the user, from the plurality of media programs that relate to the received information.

Claims

1. A computer-implemented method, comprising:

receiving, at a computer system, information expressing a user'"'"'s interest in a particular episode of a first media program that has a first series of episodes;

determining that the particular episode of the first media program has not yet aired;

identifying an alternative media program that is related to the first media program but is from a second series that differs from the first series, the identifying comprising;

identifying one or more characteristics of the first media program;

identifying one or more media programs other than the first media program based at least on the identified one or more characteristics of the first media program and a level of relevance of the one or more other media programs to the first media program; and

selecting a particular media program from the one or more media programs other than the first media program based on popularity data for the one or more media programs other than the first media program; and

generating and transmitting a recommendation of the alternative media program for display to the user based at least on the level of relevance and a popularity of the alternative media program to the first media program.

2. The method of claim 1, wherein the information expressing a user'"'"'s interest comprises an explicit query.

3. The method of claim 1, further comprising identifying information that indicates interest, by the user, in particular ones of the media programs,

wherein the generating and transmitting the recommendation is further based on the information that indicates interest, by the user, in particular ones of the media programs.

4. The method of claim 1, further comprising obtaining information that indicates a popularity of the identified one or more other media programs,

wherein the generating the recommendation includes ranking the one or more media programs based on the information indicative of popularity of the identified one or more other media programs.

5. The method of claim 1, further comprising identifying interests of other users having profiles similar to the user,

wherein the generating and transmitting the recommendation is further based on the identified interest of the other users.

6. The method of claim 1, wherein identifying the one or more other media programs comprises determining that the first media program and at least one of the one or more other media programs share one or more actors.

7. The method of claim 1, wherein identifying the one or more other media programs comprises determining that the first media program and at least one of the one or more other media programs share a particular genre.

8. The method of claim 1, further comprising determining correlations between the first media program and each of the at least one or more other media programs,

wherein the generating and transmitting the recommendation is further based on the determined correlations between the first media program and each of the at least one or more other media programs.

9. The method of claim 1, wherein the recommendation includes information about the one or more other media programs and is based at least in part on a popularity of the one or more other media programs.

10. The method of claim 1, further comprising generating data for displaying an electronic program guide grid that includes the recommendation.

11. A computer-implemented system, comprising:

memory storing data relating to popularity of one or more media programs;

an interface configured to;

receive media-related requests, wherein each media-related request includes a particular episode of a first media program that has a first series of episodes,

for each media-related request, determine that the particular episode of the first media program has not yet aired,

for each media-related request, identify an alternative media program that is related to the first media program but is from a second series that differs from the first series, wherein the identifying comprises identifying one or more characteristics of the particular first media program associated with the particular media-related request, identifying one or more media programs other than the first media program based at least on the identified one or more characteristics of the first media program and a level of relevance of the one or more other media programs to the first media program, and selecting a particular media program from the one or more media programs other than the first media program based on popularity data for the one or more media programs other than the first media program, and

generate recommendations in response to the media-related requests, wherein, for each media-related request, the recommendation includes the particular alternative media program; and

a programming guide builder to generate code for constructing a programming guide containing media programs responsive to the media-related requests.

12. A non-transitory computer-readable medium storing software comprising instructions executable by one or more computers which, upon such execution, cause the one or more computers to perform operations comprising:

receiving information expressing a user'"'"'s interest in a particular episode of a first media program that has a first series of episodes;

determining that the particular episode of the first media program has not yet aired;

identifying an alternative media program that is related to the first media program but is from a second series that differs from the first series, the identifying comprising;

identifying one or more characteristics of the first media program;

identifying one or more media programs other than the first media program based at least on the identified one or more characteristics of the first media program and a level of relevance of the one or more other media programs to the first media program; and

selecting a particular media program from the one or more media programs other than the first media program based on popularity data for the one or more media programs other than the first media program; and

generating and transmitting a recommendation of the alternative media program for display to the user based at least on the level of relevance and a popularity of the alternative media program to the first media program.

13. The non-transitory computer-readable medium of claim 12, the operations further comprising identifying information that indicates interest, by the user, in particular ones of the media programs,

wherein the generating and transmitting the recommendation is further based on the information that indicates interest, by the user, in particular ones of the media programs.

14. The non-transitory computer-readable medium of claim 12, the operations further comprising obtaining information that indicates a popularity of the identified one or more other media programs,

wherein the generating the recommendation includes ranking the one or more media programs based on the information indicative of popularity of the identified one or more other media programs.

15. The non-transitory computer-readable medium of claim 12, operations further comprising identifying interests of other users having profiles similar to the user,

wherein the generating and transmitting the recommendation is further based on the identified interest of the other users.

16. The non-transitory computer-readable medium of claim 12, wherein identifying the one or more other media programs comprises determining that the first media program and at least one of the one or more other media programs share one or more actors.

17. The non-transitory computer-readable medium of claim 12, wherein identifying the one or more other media programs comprises determining that the first media program and at least one of the one or more other media programs share a particular genre.

18. The non-transitory computer-readable medium of claim 12, the operations further comprising determining correlations between the first media program and each of the at least one or more other media programs,

wherein the generating and transmitting the recommendation is further based on the determined correlations between the first media program and each of the at least one or more other media programs.

19. The non-transitory computer-readable medium of claim 12, the operations further comprising generating data for displaying an electronic program guide grid that includes the recommendation.

20. The non-transitory computer-readable medium of claim 12, wherein the information expressing a user'"'"'s interest comprises an explicit query.