Adaptive Ad Server

• US 20090063249A1
• Filed: 09/04/2007
• Published: 03/05/2009
• Est. Priority Date: 09/04/2007
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Wiggins, Ralphe, Tomlin, John Anthony
• Application Number:
  US11/849,811
• Publication Number:
  US 20090063249A1
• 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 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• CPC Class Codes: G06Q 30/0225 Avoiding frauds
• CPC Class Codes: G06Q 30/0226 Incentive systems for frequent usage, e.g. frequent flyer miles programs or point systems
• CPC Class Codes: G06Q 30/0239 Online discounts or incentives

Abstract

A system is disclosed for distributing an ad to a user. The system may include and advertisement database for maintaining a plurality of advertisements, and a user profile database for maintaining a plurality of user profiles. The system may also include an advertisement server coupled with the advertisement database and the user profile database, the advertisement server operable to: receive a first set of information indicative of a user profile; receive a second set of information indicative of an ad property; receive a third set of information indicative of a plurality of advertisements; determine, based on the user profile, a user group for the user, the user group having an associated probability of an action in relation to an advertisement; select, based on the determined user group and the ad property, an advertisement from the plurality of advertisements for placement in the ad property; and deliver the selected advertisement at the ad property to the user.

Claims

1. A method for delivering an advertisement to a user, comprising:

receiving a first set of information indicative of a user profile;

receiving a second set of information indicative of an ad property;

receiving a third set of information indicative of a plurality of advertisements;

determining, based on the user profile, a user group for the user, the user group having an associated probability of an action in relation to an advertisement;

selecting, based on the determined user group and the ad property, an advertisement from the plurality of advertisements for placement in the ad property; and

delivering the selected advertisement at the ad property to the user.

2. The method of claim 1, where the plurality of advertisements include third party advertisements and house business advertisements.

3. The method of claim 2, where the selected advertisement is selected, in part, based on an expected revenue generated by at least one house business advertisement.

4. The method of claim 1, where the action is one selected from the group comprising a click, a conversion, or any combination thereof.

5. The method of claim 1, further comprising determining the average probability associated with the user group.

6. The method of claim 5, where the determining the average probability includes:

maintaining user profile information for each of a plurality of users, the user profile information including a bit vector;

solving a logistic regression model based on the bit vectors of user profile information and historical advertisement related activities for the user;

determining, for each user profile of a plurality of user profiles, the inner product of the logistic regression solution and each of the user profiles;

segmenting the plurality of users into user groups; and

determining an average probability for each of the user groups in accordance with the determined inner products.

7. The method of claim 6, further comprising:

determining, by solving a linear programming model based on the determined average probabilities, a distribution for the plurality of ads.

8. The method of claim 7, where the distribution is determined based on a constraint selected from the group comprising a temporal constraint, a geographic constraint, or any combination thereof.

9. The method of claim 1, further comprising determining an optimal user group for the ad property.

10. The method of claim 1, further comprising limiting the maximum delivery of the selected advertisement in a period of time.

11. A system for distributing an ad to a user, comprising:

an advertisement database to maintain a plurality of advertisements;

a user profile database to maintain a plurality of user profiles;

an advertisement server coupled with the advertisement database and the user profile database, the advertisement server operable to;

receive a first set of information indicative of a user profile;

receive a second set of information indicative of an ad property;

receive a third set of information indicative of a plurality of advertisements;

determine, based on the user profile, a user group for the user, the user group having an associated probability of an action in relation to an advertisement;

select, based on the determined user group and the ad property, an advertisement from the plurality of advertisements for placement in the ad property; and

deliver the selected advertisement at the ad property to the user.

12. The system of claim 11, where the plurality of advertisements include third party advertisements and house business advertisements.

13. The system of claim 12, where the selected advertisement is selected, in part based on an expected revenue generated by at least one house business advertisement.

14. The system of claim 11, where the action is one selected from the group comprising a click, a conversion, or any combination thereof.

15. The system of claim 11, further comprising a historical data analysis server coupled with the user profile database, the historical data analysis server operable to determine the average probability associated with the user group.

16. The system of claim 15, where the user profile database maintains user profile information for each of a plurality of users, the user profile information including a bit vector,

the system further comprising a historical data database for maintaining historical advertisement related activities for the users, where the historical data analysis server is further coupled to the historical data database, and where the historical data analysis server is further operable to:

solve a logistic regression model based on the bit vectors of user profile information and historical advertisement related activities for the users;

determine, for each user profile of a plurality of user profiles, the inner product of the logistic regression solution and each of the user profiles;

segment the plurality of users into user groups; and

determine an average probability for each of the user groups in accordance with the determined inner products.

17. The system of claim 16, where the advertisement server is further operable to:

determine, by solving a linear programming model based on the determined average probabilities, a distribution for the plurality of ads.

18. The system of claim 17, where the distribution is determined based on a constraint selected from the group comprising a temporal constraint, a geographic constraint, or any combination thereof.

19. The system of claim 11, where the advertisement server is further operable to determine an optimal user group for the ad property.

20. The system of claim 11, where the advertisement server is further operable to limit the maximum delivery of the selected advertisement in a period of time.