Trust Network Based Advertising System

• US 20100030638A1
• Filed: 09/24/2007
• Published: 02/04/2010
• Est. Priority Date: 09/22/2006
• Status: Abandoned Application

• Current Assignee: Eric Moe, John Stannard Iii Davis
• Original Assignee: Eric Moe, John Stannard Iii Davis
• Inventors: Moe, Eric, Davis, John Stannard III
• Application Number:
  US12/442,525
• Publication Number:
  US 20100030638A1
• Time in Patent Office: Days
• US Class Current: 705/14.430
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0245 Surveys
• CPC Class Codes: G06Q 30/0254 based on statistics
• CPC Class Codes: G06Q 30/0277 Online advertisement

Abstract

The inventive system uses a trust network rating system to target advertisements thereby increasing the effectiveness as well as the palatability of the advertisement. A user of an online system sets up a trust network by indicating criteria whereby the user trusts other users. Ratings made by the other users of goods or services are evaluated according to the particular trust network the user has set up. The user receives advertisements only from those vendors who have met thresholds based on the evaluated ratings. This ensures that the user receives only pertinent and interesting advertisements so that the user is more likely to respond positively to the advertisements.

Claims

1. A method for automatically selecting advertisements appropriate for a user of a system wherein one or more computers execute a program comprising the steps of:

creating a social network comprising;

linking users directly to said network according to indication of association between users;

linking users indirectly to said network according to indication of association with directly linked users; and

linking users indirectly to said network according to indication of association with other indirectly linked users;

using said network to infer and calculate trust between linked users thereby inferring and calculating a Personal trust network for each user that is Personal to each user; and

delivering advertisements for items or services to users whose personal trust networks include users who have already provided the ratings or recommendations for the advertised items or services, so that the advertisements are more likely to be appropriate to the users receiving the advertisements.

2. The method according to claim 1, wherein identity of the users providing the recommendations or ratings for items or services is not revealed to the users receiving the advertisements, thereby allowing rating or recommendation sources to be anonymous.

5. The method according to claim 1, wherein the system is part of a website.

19. The method according to claim 1, wherein a calculated personal trust network rating for the advertised item or service is delivered along with the advertisement.

20. The method according to claim 1, wherein a calculated personal trust network trust level for the users who have already provided the ratings or recommendations for the advertised items or services is delivered along with the advertisement.

21. The method according to claim 1, wherein the users receiving advertisements provide feedback to the system regarding the items or services being advertised.

22. The method according to claim 21, wherein the feedback provided by the users receiving advertisements is used to adjust the calculated personal trust network thereby adjusting and improving the users calculated personal trust networks and making them more accurate and valuable.

23. The method according to claim 21, wherein the feedback provided by the users receiving advertisements is used to adjust or filter future advertisements delivered to the users.

3. (canceled)

4. (canceled)

6. (canceled)

7. A method for controlling the delivery of advertising to users of a system wherein one or more computers execute a program comprising the steps of:

a first user indicating contextual trust in at least one other user which has indicated mutual contextual trust;

the at least one other user providing ratings for at least one item or service not yet rated by the first user;

computing effective ratings for said item or service based on the mutual contextual trust and the ratings of the at least one other user; and

delivering advertisements for said rated item or service to the first user wherein the step of delivering is controlled by filtering criteria which include the effective rating.

8. The method according to claim 7, wherein the first user determines the filtering criteria.

9. The method according to claim 7, wherein advertisers determine the filtering criteria.

10. The method according to claim 7, wherein the system determines the filtering criteria.

11. The method according to claim 10, wherein the system is part of a website.

12. The method according to claim 10, wherein the system a combination of a separate trust network based rating system and a separate advertisement engine.

13. (canceled)

14. (canceled)

15. (canceled)

16. (canceled)

17. (canceled)

18. (canceled)

24. A computerized system for selecting advertisements to transmit to specific recipients wherein one or more computers execute a program comprising the steps of:

creating or using an explicit trust network comprising;

linking users directly according to indication of trust between users;

linking users indirectly according to common indication of trust with other users who are directly linked; and

linking users indirectly according to commonly shared indirect trust of linked users;

determining a personal trust network for each network user that is personal to each user by using the trust network to calculate trust between linked users thereby;

using implicit or explicit recommendations or ratings for items or services by the trust network users to deliver advertisements to other users whose personal trust networks include the users that have already provided the ratings or recommendations for items or services,

thereby providing advertisements to individual users for items or services that are recommended or rated by one or more members of their personal trust network.

25. The system according to claim 24, wherein the identity of the users providing the recommendations or ratings for items or services is not revealed to the users receiving the advertisements, thereby allowing the rating or recommendation sources to be anonymous.

26. The system according to claim 24, wherein a calculated personal trust network rating for the advertised item or service is also indicated along with the advertisement.

27. The system according to claim 24, wherein a calculated personal trust network trust level for the item or service raters is delivered along with the advertisement.

28. The system according to claim 24, wherein the users receiving advertisements provide feedback regarding the items or services being advertised.

29. The system according to claim 28, wherein the feedback provided by the users receiving advertisements is used to adjust their calculated personal trust network, thereby adjusting and improving the calculated personal trust networks and making them more accurate and valuable.

30. The system according to claim 28, wherein the feedback provided by the users receiving advertisements is used to adjust or filter future advertisements delivered to the user.