Activity based users' interests modeling for determining content relevance

• US 8,612,435 B2
• Filed: 07/16/2009
• Issued: 12/17/2013
• Est. Priority Date: 07/16/2009
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Sambrani, Hemanth, Monga, Rohan, Vasudevan, Sudharsan, Gupta, Sanjeev
• Primary Examiner(s): Pham, Hung Q
• Assistant Examiner(s): CHEUNG, HUBERT G
• Application Number:
  US12/504,527
• Publication Number:
  US 20110016121A1
• Time in Patent Office: 1,615 Days
• Field of Search: None
• US Class Current: 707/734
• CPC Class Codes: G06F 16/337 Profile generation, learning or modification
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising

Abstract

A method and apparatus for activity-based users'"'"' interests modeling for determining relevance of the content distributed to the users is provided. Modeling of the user'"'"'s interests starts by collecting information about the actions that the user performed and about the contents that were associated with the actions. That information may be used to determine how much interest the user has had in the individual subjects up to date, and to determine which subjects became more or less important to the user over time. Further processing of the information about the interests of each of the individual users in a group of users may produce characteristics indicating the interests of the group as a whole. Additional processing may generate the information reflecting relative importance of the interests of an individual user in the group to the interests of other users in the same group.

Claims

1. A method comprising:

monitoring actions performed by a user that is associated with a profile target;

wherein said profile target comprises a group that includes at least two users;

maintaining, for said group, a profile that includes particular data that reflects a cumulative representation of interests that said group has had in each subject of a particular set of one or more subjects;

detecting that said user performed a particular action associated with a particular content;

wherein said particular content is related to said particular set of said one or more subjects;

wherein each subject, of said particular set of said one or more subjects, has, for said particular content, a corresponding subject weight value;

wherein, for said particular content, said corresponding subject weight value for each subject indicates how related said particular content is to said corresponding subject of said particular set of said one or more subjects;

in response to said user performing said particular action associated with said particular content, performing said steps of;

determining a particular action type of said particular action, wherein said particular action type of said particular action is one of a plurality of action types;

determining, for said user, one or more interest weights for said particular set of said one or more subjects based, at least in part, on;

one or more subject weight values, for said particular content, that correspond to said particular set of said one or more subjects, an action type weight determined for said particular action type of said particular action, and at least one demographic characteristic of said user;

updating said particular data in said profile associated with said group based, at least in part, on said one or more interest weights for said particular set of said one or more subjects determined for said user;

wherein said step of updating is performed by one or more computing devices.

2. The method of claim 1, wherein said determining said one or more interest weights for said particular set of said one or more subjects is based, at least in part, on whether said user was interested in any of said one or more subjects in said particular set of said one or more subjects in the past.

3. The method of claim 1, wherein said determining said one or more interest weights for said particular set of said one or more subjects is based, at least in part, on whether said particular action is associated with a long term interest.

4. The method of claim 1, wherein said determining said one or more interest weights for said particular set of said one or more subjects is based, at least in part, on whether any user associated with said profile target was interested in any of said subjects in said particular set of said one or more subjects in the past.

5. The method of claim 1, wherein said updating said particular data in said profile associated with said group further comprises applying a decay function to said one or more interest weights for said particular set of said one or more subjects.

6. The method of claim 1, wherein said user has one or more associated demographic characteristics that are specific to said profile target.

7. The method of claim 6, wherein said updating said particular data in said profile associated with said group further comprises modifying said one or more interest weights for said particular set of said one or more subjects based on said one or more demographic characterstics associated with said user.

8. One or more non-transitory storage media storing instructions which, when executed by one or more computing devices, cause performance of steps comprising:

monitoring actions performed by a user that is associated with a profile target;

wherein said profile target comprises a group that includes at least two users;

maintaining, for said group, a profile that includes particular data that reflects a cumulative representation of interests that said group has had in each subject of a particular set of one or more subjects;

detecting that said user performed a particular action associated with a particular content;

wherein said particular content is related to said particular set of said one or more subjects;

wherein each subject, of said particular set of said one or more subjects, has, for said particular content, a corresponding subject weight value;

wherein, for said particular content, said corresponding subject weight value for each subject indicates how related said particular content is to said corresponding subject of said particular set of said one or more subjects;

in response to said user performing said particular action associated with said particular content, performing said steps of;

determining a particular action type of said particular action, wherein said particular action type of said particular action is one of a plurality of action types;

determining, for said user, one or more interest weights for said particular set of said one or more subjects based, at least in part, on;

one or more subject weight values, for said particular content, that correspond to said particular set of said one or more subjects, an action type weight determined for said particular action type of said particular action, and at least one demographic characteristic of said user;

updating said particular data in said profile associated with said group based, at least in part, on said one or more interest weights for said particular set of said one or more subjects determined for said user.

9. The one or more non-transitory storage media of claim 8, wherein instructions which cause performance of said determining said one or more interest weights for said particular set of said one or more subjects further comprise instructions which, when executed, cause performance of said determining based, at least in part, on whether said user was interested in any of said one or more subjects in said particular set of said one or more subjects in the past.

10. The one or more non-transitory storage media of claim 8, wherein said instructions which cause performance of said determining said determining said one or more interest weights for said particular set of said one or more subjects further comprise instructions, which, when executed, cause performance of said determining based, at least in part, on whether said particular action is associated with a long term interest.

11. The one or more non-transitory storage media of claim 8, wherein said instructions which cause performance of said determining said one or more interest weights for said particular set of said one or more subjects further comprise instructions which, when executed, cause performance of said determining based, at least in part, on whether any user associated with said profile target was interested in any of said subjects in said particular set of said one or more subjects in the past.

12. The one or more non-transitory storage media of claim 8, wherein said instructions which cause performance of said updating said particular data in said profile associated with said group further comprise instructions which, when executed, cause performance of steps comprising applying a decay function to said one or more interest weights for said particular set of said one or more subjects.

13. The one or more non-transitory storage media of claim 8, wherein said user has one or more associated demographic characteristics that are specific to said profile target.

14. The one or more non-transitory storage media of claim 13, wherein said instructions which cause performance of said updating said particular data in said profile associated with said group further comprise instructions which, when executed, cause performance of steps comprising:

modifying said one or more interest weights for said particular set of said one or more subjects based on said one or more demographic characteristics associated with said user.

15. A method comprising:

monitoring actions performed by a user that is associated with a profile target;

wherein said profile target comprises a group that includes a plurality of users;

maintaining, for said group, a profile that includes particular data that reflects a cumulative representation of interests that said group has had in each subject of a particular set of one or more subjects;

detecting that said user performed a particular action associated with a particular content;

wherein said particular content is related to said particular set of said one or more subjects;

in response to said user performing said particular action associated with said particular content, performing said steps of;

determining a particular action type of said particular action, wherein said particular action type of said particular action is one of a plurality of action types;

determining, for said user, one or more interest present values for said particular set of said one or more subjects based, at least in part, on;

one or more subject weight values, for said particular content, that correspond to said particular set of said one or more subjects,

wherein, for said particular content, a corresponding subject weight value for each subject indicates how related said particular content is to said corresponding subject of said particular set of said one or more subjects, an action type weight determined for said particular action type, and at least one demographic characteristic of said user;

wherein said one or more interest present values indicate how much interest said user presently has in each subject of said particular set of said one or more subjects, identified for said particular content;

determining at least two interest past values for said particular set of said one or more subjects, identified in said particular content;

wherein said at least two interest past values indicate how much interest at least two users, of said plurality of users, previously had in each subject of said particular set of said one or more subjects;

updating, said particular data in said profile associated with said group of said plurality of users, based, at least in part, on said one or more interest present values and said at least two interest past values;

wherein said step of said updating is performed by one or more computing devices programmed to be special purpose machines pursuant to program instructions.

16. The method of claim 15, wherein said updating, said particular data in said profile associated with said group of said plurality of users further comprises applying a decay function to one or more of said at least two interest past values for said particular set of said one or more subjects.