System and method for making media recommendations

• US 20030014407A1
• Filed: 04/11/2002
• Published: 01/16/2003
• Est. Priority Date: 04/11/2001
• Status: Abandoned Application

• Current Assignee: Green Arrow Media Incorporated
• Original Assignee: Green Arrow Media Incorporated
• Inventors: Blatter, Steven G., Brown, David
• Application Number:
  US10/119,905
• Publication Number:
  US 20030014407A1
• Time in Patent Office: Days
• US Class Current: 707/6
• 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 16/435 Filtering based on additional data, e.g. user or group profiles
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A system and method generates a recommendation to a user for a media object from a plurality of media objects located in a media object database stored in a memory. Each media object includes a plurality of properties, each property having one or more values. The plurality of media objects are filtered into a filtered pool of media objects based on a user profile corresponding to the user. A plurality of target property values are selected based on the user profile, and a score is generated for each of the media objects in the filtered pool based on the selected target property values. A media object is recommended to the user from the media objects in the filtered pool based on the scores generated for each of the media objects in the filtered pool.

Claims

1. A method for generating a recommendation to a user for a media object from a plurality of media objects located in a media object database stored in a memory, wherein each media object includes a plurality of properties, each property having one or more values, the method comprising:

filtering the plurality of media objects into a filtered pool of media objects based on a user profile corresponding to the user;

selecting a plurality of target property values based on the user profile;

generating a score for each of the media objects in the filtered pool based on the selected target property values; and

recommending a media object to the user from the media objects in the filtered pool based on the scores generated for each of the media objects in the filtered pool.

2. A method according to claim 1, further comprising modifying the user profile based on the media object recommended to the user.

3. A method according to claim 2, wherein the user profile includes a preference value for each of the plurality of target property values of the recommended media object and wherein the modifying includes adjusting each preference value of the user profile based on each of the plurality of target property values of the recommended media object.

4. A method according to claim 1, wherein the number of media objects in the filtered pool is less than the number of media objects in the media object database.

5. A method according to claim 1, wherein each media object is any one of a song, an album, a music video, a movie, a radio station, a TV station, a TV show, a book, and a video game.

6. A method according to claim 1, further comprising:

identifying each preference value in the user profile that has a zero value; and

excluding a media object from the filtered pool of media objects if the media object has a media property value corresponding to an identified preference value having a zero value.

7. A method according to claim 1, wherein the user profile includes a preference value for each possible property value of a media object.

8. A method according to claim 1, further comprising:

selecting a property in the user profile;

calculating a total of the preference values of each property value in the user profile;

generating a random number between zero and the calculated total; and

selecting a target property value for the selected property based on the random number.

9. A method according to claim 1, further comprising:

determining if a media object from the filtered pool of media objects has a selected target property value; and

increasing a score for the media object if the media object is determined to have the selected target property value.

10. A method according to claim 9, further comprising

selecting an alternative target property value if the media object is determine not to have the selected property value;

and

increasing the score for the media object if the media object is determined to have the selected alternative target property value,

wherein the increase in the score for the media object is greater if the media object is determined to have the selected target property value as compared to if the media object is determined to have the alternative selected target property value.

11. A method according to claim 10, wherein the increase in score for the media object is adjusted with a weighting factor, and wherein a greatest weighting factor is used if the media object has the selected target property value.

12. A method according to claim 1, further comprising:

ordering the media objects from the filtered pool of media objects according to the generated scores;

selecting a media object according to the order;

determining if the selected media object satisfies one or more minimum separation rules; and

recommending the selected media object if it satisfies the one or more minimum separation rules.

13. A method according to claim 12, wherein the a first one of the one or more minimum separation rules determines if the selected media object has already been recommended to the user in less than a predetermined number of recommendations identified in the user profile.

14. A method according to claim 1, further comprising:

providing one or more questions to the user;

receiving responses to each of the questions provided to the user; and

modifying the user profile based on the received responses,

wherein at least one of the questions provided to the user is indirectly related to the media preferences of the user.

16. A computer system according to claim 15, the memory further comprising an instruction configured to modify the user profile based on the media object recommended to the user.

17. A computer system according to claim 16, wherein the user profile includes a preference value for each of the plurality of target property values of the recommended media object, the memory further comprising an instruction configured to adjust each preference value of the user profile based on each of the plurality of target property values of the recommended media object.

18. A computer system according to claim 15, wherein the number of media objects in the filtered pool is less than the number of media objects in the media object database.

19. A computer system according to claim 15, wherein each media object is any one of a song, an album, a music video, a movie, a radio station, a TV station, a TV show, a book, and a video game.

20. A computer system according to claim 15, the memory further comprising instructions configured to:

identify each preference value in the user profile that has a zero value; and

exclude a media object from the filtered pool of media objects if the media object has a media property value corresponding to an identified preference value having a zero value.

21. A computer system according to claim 15, wherein the user profile includes a preference value for each possible property value of a media object.

22. A computer system according to claim 15, the memory further comprising instructions configured to:

select a property in the user profile;

calculate a total of the preference values of each property value in the user profile;

generate a random number between zero and the calculated total; and

select a target property value for the selected property based on the random number.

23. A computer system according to claim 15, the memory further comprising instructions configured to:

determine if a media object from the filtered pool of media objects has a selected target property value; and

increase a score for the media object if the media object is determined to have the selected target property value.

24. A computer system according to claim 23, the memory further comprising instructions configured to:

select an alternative target property value if the media object is determine not to have the selected property value; and

increase the score for the media object if the media object is determined to have the selected alternative target property value,

wherein the increase in the score for the media object is greater if the media object is determined to have the selected target property value as compared to if the media object is determined to have the alternative selected target property value.

25. A computer system according to claim 24, wherein the increase in score for the media object is adjusted with a weighting factor, and wherein a greatest weighting factor is used if the media object has the selected target property value.

26. A computer system according to claim 15, the memory further comprising instructions configured to:

order the media objects from the filtered pool of media objects according to the generated scores;

select a media object according to the order;

determine if the selected media object satisfies one or more minimum separation rules; and

recommend the selected media object if it satisfies the one or more minimum separation rules.

27. A computer system according to claim 26, wherein the a first one of the one or more minimum separation rules determines if the selected media object has already been recommended to the user in less than a predetermined number of recommendations identified in the user profile.

28. A computer system according to claim 15, the memory further comprising instructions configured to:

provide one or more questions to the user;

receive responses to each of the questions provided to the user; and

modify the user profile based on the received responses,

wherein at least one of the questions provided to the user is indirectly related to the media preferences of the user.

30. A computer readable medium according to claim 29, the computer readable medium further configured to modify the user profile based on the media object recommended to the user.

31. A computer readable medium according to claim 30, wherein the user profile includes a preference value for each of the plurality of target property values of the recommended media object, the computer readable medium further configured to adjust each preference value of the user profile based on each of the plurality of target property values of the recommended media object.

32. A computer readable medium according to claim 29, wherein the number of media objects in the filtered pool is less than the number of media objects in the media object database.

33. A computer readable medium according to claim 29, wherein each media object is any one of a song, an album, a music video, a movie, a radio station, a TV station, a TV show, a book, and a video game.

34. A computer readable medium according to claim 29, the computer readable medium further configured to:

identify each preference value in the user profile that has a zero value; and

exclude a media object from the filtered pool of media objects if the media object has a media property value corresponding to an identified preference value having a zero value.

35. A computer readable medium according to claim 29, wherein the user profile includes a preference value for each possible property value of a media object.

36. A computer readable medium according to claim 29, the computer readable medium further configured to:

select a property in the user profile;

calculate a total of the preference values of each property value in the user profile;

generate a random number between zero and the calculated total; and

select a target property value for the selected property based on the random number.

37. A computer readable medium according to claim 29, the computer readable medium further configured to:

determine if a media object from the filtered pool of media objects has a selected target property value; and

increase a score for the media object if the media object is determined to have the selected target property value.

38. A computer readable medium according to claim 37, the computer readable medium further configured to:

select an alternative target property value if the media object is determine not to have the selected property value; and

increase the score for the media object if the media object is determined to have the selected alternative target property value,

wherein the increase in the score for the media object is greater if the media object is determined to have the selected target property value as compared to if the media object is determined to have the alternative selected target property value.

39. A computer readable medium according to claim 38, wherein the increase in score for the media object is adjusted with a weighting factor, and wherein a greatest weighting factor is used if the media object has the selected target property value.

40. A computer readable medium according to claim 29, the computer readable medium further configured to:

order the media objects from the filtered pool of media objects according to the generated scores;

select a media object according to the order;

determine if the selected media object satisfies one or more minimum separation rules; and

recommend the selected media object if it satisfies the one or more minimum separation rules.

41. A computer readable medium according to claim 40, wherein the a first one of the one or more minimum separation rules determines if the selected media object has already been recommended to the user in less than a predetermined number of recommendations identified in the user profile.

42. A computer readable medium according to claim 29, the computer readable medium further configured to:

provide one or more questions to the user;

receive responses to each of the questions provided to the user; and

modify the user profile based on the received responses,

wherein at least one of the questions provided to the user is indirectly related to the media preferences of the user.

15. A computer system for generating a recommendation to a user for a media object from a plurality of media objects located in a media object database stored in a memory, wherein each media object includes a plurality of properties, each property having one or more values, the computer system comprising:

a processor; and

a memory comprising a plurality of instructions executed by the processor, the plurality of instructions configured to;

filter the plurality of media objects into a filtered pool of media objects based on a user profile corresponding to the user;

select a plurality of target property values based on the user profile;

generate a score for each of the media objects in the filtered pool based on the selected target property values; and

recommend a media object to the user from the media objects in the filtered pool based on the scores generated for each of the media objects in the filtered pool.

29. A computer readable medium operable on a computer system configured to generate a recommendation to a user for a media object from a plurality of media objects located in a media object database stored in a memory, wherein each media object includes a plurality of properties, each property having one or more values, the computer readable medium configured to:

filter the plurality of media objects into a filtered pool of media objects based on a user profile corresponding to the user;

select a plurality of target property values based on the user profile;

generate a score for each of the media objects in the filtered pool based on the selected target property values; and

recommend a media object to the user from the media objects in the filtered pool based on the scores generated for each of the media objects in the filtered pool.