REPUTATION SCORING

• US 20090070130A1
• Filed: 04/22/2008
• Published: 03/12/2009
• Est. Priority Date: 09/12/2007
• Status: Abandoned Application

• Current Assignee: eBay Inc.
• Original Assignee: eBay Inc.
• Inventors: Sundaresan, Neelakantan, Shen, Zeqian
• Application Number:
  US12/107,250
• Publication Number:
  US 20090070130A1
• Time in Patent Office: Days
• US Class Current: 705/319
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

In one example embodiment, a system and method is shown that includes receiving a feedback score relating to a transaction engaged in by a user. The system and method also includes applying a weight to the feedback score based on weighting criteria to create a weighted feedback score. Further, generating a reputation score for the user based on the weighted feedback score may also be implemented. In an additional example embodiment, the system and method includes identifying a reputation score relating at least one neighbor of a user, the at least one neighbor of the user including another user with whom the user has engaged in a transaction. Further, the system and method includes ordering the reputation score relating to at least one neighbor of the user to create an ordered reputation score. Moreover, the system and method includes displaying the ordered reputation score.

Claims

1. A computer implemented method comprising:

receiving a feedback score relating to a transaction engaged in by a user;

applying a weight to the feedback score based on weighting criteria to create a weighted feedback score; and

generating a reputation score for the user based on the weighted feedback score.

2. The computer implemented method of claim 1, further comprising updating a reputation score of a neighbor of the user using the reputation score for the user, the neighbor including another user with whom the user has engaged in a transaction.

3. The computer implemented method of claim 1, further comprising:

identifying a weighted feedback score for at least one neighbor, the at least one neighbor including another user with whom the user has engaged in a transaction;

determining a sum of the weighted feedback score for the at least one neighbor; and

identifying the reputation score for the user by determining a sum of the weighted feedback score for the at least one neighbor and a seed value.

4. The computer implemented method of claim 1, wherein the weighting criteria includes at least one of a qualification of another user, a monetary value of a transaction engaged in by another user, or a frequency of transactions conducted by another user.

5. The computer implemented method of claim 1, further comprising determining a vector score through finding a product of a further vector score and a feedback matrix, the feedback matrix including at least one feedback score for at least one user.

6. The computer implemented method of claim 5, wherein the further vector score includes a product of the weighted feedback score and the reputation score.

7. The computer implemented method of claim 5, wherein the feedback matrix is an adjacency matrix.

8. A computer implemented method comprising:

identifying a reputation score relating at least one neighbor of a user, the at least one neighbor of the user including another user with whom the user has engaged in a transaction;

ordering the reputation score relating to at least one neighbor of the user to create an ordered reputation score; and

displaying the ordered reputation score.

9. The computer implemented method of claim 8, wherein the ordering includes ordering the reputation score in an order including at least one of ordering by highest to lowest reputation score, or ordering by lowest to highest reputation score.

10. The computer implemented method of claim 8, further comprising displaying a graph that includes a node and an edge, the node including the reputation score relating to the at least one neighbor, and the node and the edge distinguished by at least one distinguishing characteristic including a color, a shape, or a pattern.

11. A computer system comprising:

a receiver to receive a feedback score relating to a transaction engaged in by a user;

a weighting engine to apply a weight to the feedback score based on weighting criteria to create a weighted feedback score; and

a reputation score generator to generate a reputation score for the user based on the weighted feedback score.

12. The computer system of claim 11, further comprising a reputation score update engine to update a reputation score of a neighbor of the user using the reputation score for the user, the neighbor includes another user with whom the user has engaged in a transaction.

13. The computer system of claim 11, further comprising:

a first identification engine to identify a weighted feedback score for at least one neighbor, the at least one neighbor that includes another user with whom the user has engaged in a transaction;

a calculation engine to determine a sum of the weighted feedback score for the at least one neighbor; and

a second identification engine to identify the reputation score for the user through a determination of a sum of the weighted feedback score for the at least one neighbor and a seed value.

14. The computer system of claim 11, wherein the weighting criteria includes at least one of a qualification of another user, a monetary value of a transaction engaged in by another user, or a frequency of transactions conducted by another user.

15. The computer system of claim 11, further comprising a vector score engine to determine a vector score through finding a product of a further vector score and a feedback matrix, the feedback matrix including at least one feedback score for at least one user.

16. The computer system of claim 15, wherein the further vector score includes a product of the weighted feedback score and the reputation score.

17. The computer system of claim 15, wherein the feedback matrix is an adjacency matrix.

18. A computer system comprising:

a reputation score engine to identify a reputation score relating at least one neighbor of a user, the at least one neighbor of the user that includes another user with whom the user has engaged in a transaction;

an ordering engine to order the reputation score that relates to at least one neighbor of the user to create an ordered reputation score; and

a display to display the ordered reputation score.

19. The computer system of claim 18, wherein the order includes the reputation score in an order including at least one of an order by highest to lowest reputation score, or ordering by lowest to highest reputation score.

20. The computer system of claim 18, further comprising a display to display a graph that includes a node and an edge, the node to include the reputation score for at least one neighbor, and the node and the edge distinguished by at least one distinguishing characteristic that includes a color, a shape, or a pattern.

21. An apparatus comprising:

means for receiving a feedback score relating to a transaction engaged in by a user;

means for applying a weight to the feedback score based on weighting criteria to create a weighted feedback score; and

means for generating a reputation score for the user based on the weighted feedback score.

22. A machine-readable medium comprising instructions, which when implemented by one or more machines, cause the one or more machines to perform the following operations:

receive a feedback score relating to a transaction engaged in by a user;

apply a weight to the feedback score based on weighting criteria to create a weighted feedback score; and

generate a reputation score for the user based on the weighted feedback score.