Recommending video programs

• US 9,396,258 B2
• Filed: 01/22/2009
• Issued: 07/19/2016
• Est. Priority Date: 01/22/2009
• Status: Active Grant

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Chu, Michael, Baluja, Shumeet
• Primary Examiner(s): Lewis, Jonathan V
• Application Number:
  US12/358,120
• Publication Number:
  US 20100186041A1
• Time in Patent Office: 2,735 Days
• Field of Search: 725/46, 725/34
• US Class Current: 1/1
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/70 of video data
• CPC Class Codes: G06F 16/735 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06F 16/7867 using information manually generated, e.g. tags, keywords, comments, title and artist information, manually generated time, location and usage information, user ratings
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: H04N 21/2408 Monitoring of the upstream path of the transmission network, e.g. client requests monitoring data switching networks utilization H04L43/0876; scheduling or organising the servicing of application requests H04L67/60
• 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 21/2665 Gathering content from different sources, e.g. Internet and satellite
• 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 21/47 End-user applications
• CPC Class Codes: H04N 21/482 End-user interface for program selection broadcast systems using EPGs H04H60/72
• 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 21/6125 involving transmission via Internet transmission by internet of broadcast information H04H60/82
• CPC Class Codes: H04N 21/6175 involving transmission via Internet broadcast-related systems characterised by the transmission system being the Internet H04H60/82
• CPC Class Codes: H04N 21/6581 Reference data, e.g. a movie identifier for ordering a movie or a product identifier in a home shopping application
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38
• CPC Class Codes: H04N 21/812 involving advertisement data advertising per se G06Q30/02
• CPC Class Codes: H04N 7/163 by receiver means only
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

A system and method for recommending video programs to a user comprising determining a first video program that is of interest to a user and then determining a second video program to recommend to the user, the second video program being determined from a recommendation database assembled by analyzing access logs from one or more search engines or online video content providers.

Claims

1. A computer-implemented method for recommending a video program to a user comprising:

storing a database of video program information including information identifying related video programs, wherein the related video programs are determined based upon analysis of user interactions with an internet search engine or online video content provider;

receiving, from a first user device, an indication of a first video program;

identifying a plurality of video programs related to the first video program based on the information identifying related video programs and the received indication, wherein each of the plurality of video programs corresponds to at least one of a plurality of types of user interactions related to the first video program, wherein the plurality of types of user interactions are received from a plurality of user devices other than the first user device, and wherein each of the plurality of types of user interactions is associated with an assigned weight;

determining, for each combination of the first video program and one of the plurality of video programs, a frequency count that indicates a number of times each combination occurs in connection with each type of user interaction;

ranking the plurality of video programs based on the assigned weight being applied to the type of user interactions and the frequency counts;

determining a second video program related to the first video program from the plurality of video programs based on the ranking; and

providing the user with a recommendation for the second video program;

wherein the plurality of types of user interactions comprise streaming of at least one video program.

2. The method of claim 1 further comprising storing an identifier of the first video program in a user profile of the user.

3. The method of claim 1 further comprising storing an identifier of the second video program in a user profile of the user.

4. The method of claim 1, wherein receiving an indication of the first video program comprises accessing a user profile to obtain an identifier of the video program.

5. The method of claim 1, wherein receiving an indication of the first video program comprises receiving information about a video program currently being presented to the user.

6. The method of claim 1, wherein receiving an indication of the first video program comprises receiving information about a video program from a client device of the user coupled to a network.

7. The method of claim 1, wherein providing the user with a recommendation for the second video program comprises providing the user with the content of the video program.

8. The method of claim 1, wherein:

receiving an indication of a first video program comprises receiving an indication of a first video program from a client coupled to a network; and

providing the user with a recommendation comprises providing a recommendation to the client coupled to the network.

9. The method of claim 1, wherein:

receiving an indication of a first video program comprises accessing a user profile of the user; and

providing the user with a recommendation comprises providing a recommendation to a client coupled to a network.

10. The method of claim 1, wherein:

receiving an indication of a first video program comprises receiving an indication of a first video program from a first client coupled to a network; and

providing the user with a recommendation comprises providing a recommendation to a second client coupled to the network.

11. The method of claim 1, further comprising selecting the second video program having a current broadcast time in the near future on the user'"'"'s broadcast system.

12. The method of claim 11, wherein the user'"'"'s broadcast system is determined from a user profile.

13. The method of claim 1, further comprising selecting the second video program having a current broadcast time in the near future in the user'"'"'s location.

14. The method of claim 13, wherein the user'"'"'s location is determined from a user profile.

15. The method of claim 13, wherein the user'"'"'s location is determined from the user'"'"'s IP address.

16. The method of claim 1, wherein the recommendation comprises a broadcast date, broadcast time, and broadcast channel on the user'"'"'s broadcast system for the second video program.

17. The method of claim 1, wherein providing the user with a recommendation for the second video program comprises using information from a user profile to rank the recommendations.

18. The method of claim 17 wherein information from a user profile comprises search queries for video programs or attributes of video programs and wherein ranking the recommendations comprises giving extra weight to recommendations that have attributes in common with the search queries.

19. The method of claim 17 wherein information from a user a profile comprises titles of video programs that have been downloaded or streamed and wherein ranking the recommendations comprises giving extra weight to recommendations that have attributes in common with the downloaded or streamed video programs.

20. A computer implemented system, including a processor and memory, for recommending a video program to a user, comprising:

a database of video program information including information identifying related video programs, wherein the related video programs are determined based upon analysis of user interactions with an internet search engine or online video content provider;

a first module configured to receive, from a first user device, an indication of a first video program;

a second module configured to;

identify a plurality of video programs related to the first video program based on the information identifying related video programs and the received indication, wherein each of the plurality of video programs corresponds to at least one of a plurality of types of user interactions related to the first video program, wherein the plurality of types of user interactions are received from a plurality of user devices other than the first user device, and wherein each of the plurality of types of user interactions is associated with an assigned weight,

determine, for each combination of the first video program and one of the plurality of video programs, a frequency count that indicates a number of times each combination occurs in connection with each type of user interaction,

rank the plurality of video programs based on the assigned weight being applied to the type of user interactions and the frequency counts, and

determine a second video program related to the first video program from the plurality of video programs based on the ranking; and

a third module communicatively coupled to the second module configured to provide to the user a recommendation for the second video program;

wherein the plurality of types of user interactions comprises streaming of at least one video program.

21. The system of claim 20 further comprising a second database configured to store user profiles.

22. The system of claim 20 wherein the first module is further configured to receive the indication of the first video program from a user profile of the user in the second database.

23. The system of claim 20 wherein the first module configured to receive an indication of a first video program comprises the first module configured to receive an indication of a first video program from a client device of the user coupled to a network.

24. The system of claim 20 wherein:

the first module configured to receive an indication of a first video program comprises the first module configured to receive an indication of a first video program from a client device of the user coupled to a network; and

the third module configured to provide to the user a recommendation for the second video program comprises the third module configured to provide the recommendation to the client device of the user coupled to the network.

25. The system of claim 20 wherein:

the first module configured to receive an indication of a first video program comprises the first module configured to access a user profile of the user; and

the third module configured to provide to the user a recommendation for the second video program comprises the third module configured to provide the recommendation to a client device of the user coupled to the network.

26. The system of claim 20 wherein:

the first module configured to receive an indication of a first video program comprises the first module configured to receive the indication of the first video program from a first client device of the user coupled to a network; and

the third module configured to provide to the user a recommendation for the second video program comprises the third module configured to provide the recommendation to a second client device of the user coupled to the network.

27. A non-transitory computer readable medium having computer readable program code embodied therein to recommend a video program to a user, the computer readable program code in the non-transitory computer-readable medium including:

computer readable program code to store a database of video program information including information identifying related video programs, wherein the related video programs are determined based upon analysis of user interactions with an internet search engine or online video content provider;

computer readable program code to receive, from a first user device, an indication of a first video program;

computer readable program code to identify a plurality of video programs related to the first video program based on the information identifying related video programs and the received indication, wherein each of the plurality of video programs corresponds to at least one of a plurality of types of user interactions related to the first video program, wherein the plurality of types of user interactions are received from a plurality of user devices other than the first user device, and wherein each of the plurality of types of user interactions is associated with an assigned weight;

computer readable program code to determine, for each combination of the first video program and one of the plurality of video programs, a frequency count that indicates a number of times each combination occurs in connection with each type of user interaction;

computer readable program code to rank the plurality of video programs based on the assigned weight being applied to the type of user interactions and the frequency counts;

computer readable program code to determine a second video program related to the first video program from the plurality of video programs based on the ranking; and

computer readable program code to provide the user with a recommendation for the second video program;

wherein the interaction of the user comprises the streaming of at least one video program.