Generating a degree of interest in user profile scores in a behavioral targeting system

• US 20070239517A1
• Filed: 03/29/2006
• Published: 10/11/2007
• Est. Priority Date: 03/29/2006
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Oath Inc. (Verizon Communications Inc.)
• Inventors: Yin, Hongfeng, Lin, Long-Ji, Koran, Joshua, Chung, Christina
• Application Number:
  US11/394,353
• Publication Number:
  US 20070239517A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0255 based on user history

Abstract

A behavioral targeting system determines user profiles from online activity. The system includes a plurality of models that define parameters for determining a user profile score. Event information, which comprises on-line activity of the user, is received at an entity. To generate a user profile score, a model is selected. The model comprises recency, intensity and frequency dimension parameters. The behavioral targeting system generates a user profile score for a target objective, such as brand advertising or direct response advertising. The parameters from the model are applied to generate the user profile score in a category. The behavioral targeting system has application for use in ad serving to on-line users.

Claims

1. A method for determining user behavior from online activity, said method comprising:

storing a plurality of models at an entity, wherein a model defines a plurality of parameters, and said parameters, when applied to event information, yield a score in a range of user profile scores;

receiving, at said entity, event information from at least one event, wherein said event information comprises on-line activity between said user and said entity; and

generating at least one user profile score by applying said parameters to said user event information to generate a user profile score that comprises a score in said range of user profile scores.

2. The method as set forth in claim 1, wherein generating at least one user profile score comprises generating a plurality of user profile scores on a per category basis.

3. The method as set forth in claim 2, further comprising:

selecting a category for a user from a plurality of categories based on said user profile scores of said user; and

serving content to said user based on said category selected.

4. The method as set forth in claim 2, further comprising:

selecting a category for a user from a plurality of categories based on said user profile scores of said user; and

serving an advertisement to said user based on said category selected.

5. The method as set forth in claim 2, further comprising:

generating user profile scores for a plurality of users for a plurality of categories;

ranking said user profiles scores within each of a plurality of categories on a percentile basis; and

selecting a category for a user from said categories based on said percentile based ranking.

6. The method as set forth in claim 1, further comprising converting said user profile score to an output metric.

7. The method as set forth in claim 6, wherein said output metric comprises a click-through rate.

8. A system comprising:

storage for storing a plurality of models, wherein a model defines a plurality of parameters, and said parameters, when applied to event information, yield a score in a range of user profile scores; and

at least one server at an entity, coupled to said storage, for receiving event information from at least one event, wherein said event information comprises on-line activity between said user and said entity, and for generating at least one user profile score by applying said parameters to said user event information to generate a user profile score that comprises a score in said range of user profile scores.

9. The system as set forth in claim 8, wherein said server further for generating a plurality of user profile scores on a per category basis.

10. The system as set forth in claim 9, wherein said server further for selecting a category for a user from a plurality of categories based on said user profile scores of said user, and for serving content to said user based on said category selected.

11. The system as set forth in claim 9, wherein said server further for selecting a category for a user from a plurality of categories based on said user profile scores of said user, and for serving an advertisement to said user based on said category selected.

12. The system as set forth in claim 9, wherein said server further for generating user profile scores for a plurality of users for a plurality of categories, for ranking said user profiles scores within each of a plurality of categories on a percentile basis, and for selecting a category for a user from said categories based on said percentile based ranking.

13. The system as set forth in claim 8, wherein said server further for converting said user profile score to an output metric.

14. The system as set forth in claim 13, wherein said output metric comprises a click-through rate.

15. A computer readable medium comprising a set of instructions which, when executed by a computer, cause the computer to determine user behavior from online activity, said instructions for:

storing a plurality of models at an entity, wherein a model defines a plurality of parameters, and said parameters, when applied to event information, yield a score in a range of user profile scores;

receiving, at said entity, event information from at least one event, wherein said event information comprises on-line activity between said user and said entity; and

generating at least one user profile score by applying said parameters to said user event information to generate a user profile score that comprises a score in said range of user profile scores.

16. The computer readable medium as set forth in claim 15, wherein generating at least one user profile score comprises generating a plurality of user profile scores on a per category basis.

17. The computer readable medium as set forth in claim 16, further comprising:

selecting a category for a user from a plurality of categories based on said user profile scores of said user; and

serving content to said user based on said category selected.

18. The computer readable medium as set forth in claim 16, further comprising:

selecting a category for a user from a plurality of categories based on said user profile scores of said user; and

serving an advertisement to said user based on said category selected.

19. The computer readable medium as set forth in claim 16 further comprising:

generating user profile scores for a plurality of users for a plurality of categories;

ranking said user profiles scores within each of a plurality of categories on a percentile basis; and

selecting a category for a user from said categories based on said percentile based ranking.

20. The computer readable medium as set forth in claim 15, further comprising converting said user profile score to an output metric.

21. The computer readable medium as set forth in claim 20, wherein said output metric comprises a click-through rate.