IP Library Granted Patent US 9,769,528
Granted Patent B2
US 9,769,528 · App. 14/740,698 · Granted Sep 19, 2017

Recommending media programs based on media program popularity

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Quick Facts
Patent No.
US 9,769,528
App. No.
14/740,698
Granted
Sep 19, 2017
Kind
B2
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 (49)

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.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 30, 2026
From: GOOGLE LLC
To: BLACKBERRY LIMITED
Reel/Frame 075465/0538 →
CHANGE OF NAME Recorded Oct 2, 2017
From: GOOGLE INC.
To: GOOGLE LLC
Reel/Frame 044097/0658 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 23, 2015
From: JEON, JOON-HEE; DUREAU, VINCENT; BENTING, STEVE D.; LIN, ZHENHAI; MILLER, MICHAEL W.; PATEL, MANISH G.
To: GOOGLE INC.
Reel/Frame 036166/0841 →