Methods and Apparatus to Generate Relevance Rankings for Use by a Program Selector of a Media Presentation System

• US 20090288118A1
• Filed: 05/14/2008
• Published: 11/19/2009
• Est. Priority Date: 05/14/2008
• Status: Active Grant

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: AT&T Intellectual Property I LP (AT&T, Inc.)
• Inventors: Chang, Hisao M.
• Granted Patent: US 9,077,933 B2
• Time in Patent Office: Days
• US Class Current: 725/46
• CPC Class Codes: H04N 21/252 Processing of multiple end-users' preferences to derive collaborative data
• 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 21/42203 sound input device, e.g. microphone
• 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 21/4755 for defining user preferences, e.g. favourite actors or genre retrieval personalisation and generation of user profiles for the retrieval of video data G06F16/739; user profiles in network data switching protocols H04L67/306
• 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 21/64322 IP
• 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 21/84 Generation or processing of descriptive data, e.g. content descriptors systems specially adapted for using meta-information in broadcast systems H04H60/73
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

Example methods and apparatus to generate relevance rankings for use by a program selector of a media presentation system are disclosed. An example method comprises tabulating a plurality of occurrence counts for respective ones of a plurality of terms of a program guide, each of the occurrence counts indicating a corresponding number of times each of the terms appears in the program guide, computing a plurality of relevance ranking scores for respective ones of a plurality of programs listed in the program guide based on the plurality of occurrence counts, selecting a list of programs from the program guide based on the relevance ranking scores, and outputting the list of programs.

Claims

1. A method comprising:

tabulating a plurality of occurrence counts for respective ones of a plurality of terms of a program guide, each of the occurrence counts indicating a corresponding number of times each of the terms appears in the program guide;

computing a plurality of relevance ranking scores for respective ones of a plurality of programs listed in the program guide based on the plurality of occurrence counts;

selecting a list of programs from the program guide based on the relevance ranking scores; and

outputting the list of programs.

2. The method as defined in claim 1, wherein the occurrence counts indicate the corresponding number of times each of the terms of the program appear in at least one of a program title or a program description of the program guide.

3. The method as defined in claim 1, further comprising:

receiving a search criteria; and

selecting a list of programs from the program guide based on the relevance ranking scores and the search criteria.

4. The method as defined in claim 1, further comprising weighting the plurality of relevance ranking scores based on viewership ratings.

5. The method as defined in claim 4, wherein the viewership ratings are applied on at least one of a day-of-month, a day-of-week or an hour-of-day basis.

6. The method as defined in claim 1, further comprising weighting the plurality of relevance ranking scores based on a user profile.

7. The method as defined in claim 6, wherein the list of programs is selected to include a program chosen by a user associated with a second user profile.

8. The method as defined in claim 6, wherein the user profile represents a historical watching behavior for at least one of a particular broadcaster or a particular program.

9. The method as defined in claim 6, further comprising monitoring media selections made by a user to form the user profile.

10. The method as defined in claim 9, wherein a media selection comprises at least one of a channel or a program title.

11. The method as defined in claim 6, wherein the user profile comprises a plurality of durations for respective ones of a plurality of program titles.

12. The method as defined in claim 6, wherein the user profile comprises a plurality of durations for respective ones of a plurality of channels

13. The method as defined in claim 1, wherein tabulating the plurality of occurrence counts for the respective ones of the plurality of terms comprises:

tabulating occurrence counts for each word that appears in at least one of a program title or program description; and

tabulating occurrence counts for each program title that appears in the program guide.

14. The method as defined in claim 1, further comprising computing an average of the occurrence counts for respective words that appear in a title of a first of the plurality of programs, and wherein computing the relevance ranking score for the first title comprises multiplying the average with an occurrence count for the first title.

15. The method as defined in claim 14, further comprising multiplying the occurrence count for the first title with a boost value.

16. The method as defined in claim 1, further comprising including a program chosen by a user associated with a similar user profile in the list of programs.

17. An apparatus comprising:

a relevance ranker to compute a plurality of relevance ranking scores for respective ones of a plurality of programs listed in a program guide based on a number of times that respective ones of a plurality of terms appear in the program guide;

a program selector to select a first list of programs from the program guide based on the relevance ranking scores; and

a media server to serve the first list of programs.

18. An apparatus as defined in claim 17, wherein the relevance ranker comprises:

a word frequency tabulator to compute a first plurality of occurrence counts for respective ones of the plurality of terms that appear in the program guide; and

a title occurrence tabulator to compute a second plurality of occurrence counts for respective ones of program titles that appear in the program guide; and

a title scorer to compute the plurality of relevance ranking scores for respective ones of the plurality of programs listed in the program guide based on the first and second plurality of occurrence counts.

19. An apparatus as defined in claim 18, wherein the relevance ranker further comprises a viewership ranking adjuster to adjust the computed relevance ranking scores based on viewership ratings.

20. An apparatus as defined in claim 17, wherein the program selector comprises a profile-based adjuster to weight the plurality of relevance ranking scores based on a user profile, wherein the program selector selects the first list of programs based on the largest weighted relevance ranking scores.

21. An apparatus as defined in claim 17, wherein the program selector comprises:

a search engine to identify a second list of programs based on spoken search criteria; and

a selector to select the first list of programs from the second list of programs based on the relevance ranking scores.

22. An apparatus as defined in claim 21, wherein the program selector further comprises a title identifier to identify a program chosen by a second user associated with a second user profile, wherein the selector is to include the program chosen by the second user in the first list of programs.

23. An apparatus as defined in claim 22, wherein the user profile represents a historical watching behavior for at least one of a particular channel or a particular program.

24. An article of manufacture storing machine readable instructions which, when executed, cause a machine to:

tabulate a plurality of occurrence counts for respective ones of a plurality of terms of a program guide, each of the occurrence counts indicating a corresponding number of times each of the terms appears in the program guide;

compute a plurality of relevance ranking scores for respective ones of a plurality of programs listed in the program guide based on the plurality of occurrence counts;

select a list of programs from the program guide based on the relevance ranking scores; and

output the list of programs.

25. The article of manufacture as defined in claim 24, wherein the occurrence counts indicate the corresponding number of times each of the terms of the program appear in at least one of a program title or a program description of the program guide.

26. The article of manufacture as defined in claim 24, wherein the machine readable instructions, when executed, cause the machine to:

receive a spoken search criteria; and

select a list of programs from the program guide based on the relevance ranking scores and the search criteria.

27. The article of manufacture as defined in claim 24, wherein the machine readable instructions, when executed, cause the machine to weight the plurality of relevance ranking scores based on viewership ratings.

28. The article of manufacture as defined in claim 24, wherein the machine readable instructions, when executed, cause the machine to weight the plurality of relevance ranking scores based on a user profile.

29. The article of manufacture as defined in claim 24, wherein the machine readable instructions, when executed, cause the machine to tabulate the plurality of occurrence counts for the respective ones of the plurality of terms by:

tabulating occurrence counts for each word that appears in at least one of a program title or program description; and

tabulating occurrence counts for each program title that appears in the program guide.

30. The article of manufacture as defined in claim 24, wherein the machine readable instructions, when executed, cause the machine to:

compute an average of the occurrence counts for respective words that appear in a title of a first of the plurality of programs; and

compute the relevance ranking score for the first title by multiplying the average with an occurrence count for the first title.

31. The article of manufacture as defined in claim 24, wherein the machine readable instructions, when executed, cause the machine to include a program chosen by a user associated with a similar user profile in the list of programs.