ANTI-COLLUSIVE VOTE WEIGHTING

• US 20090150229A1
• Filed: 12/05/2008
• Published: 06/11/2009
• Est. Priority Date: 12/05/2007
• Status: Abandoned Application

• Current Assignee: Gary S. Shuster
• Original Assignee: Gary S. Shuster
• Inventors: SHUSTER, Gary Stephen
• Application Number:
  US12/329,296
• Publication Number:
  US 20090150229A1
• Time in Patent Office: Days
• US Class Current: 705/12
• CPC Class Codes: G07C 13/00 Voting apparatus

Abstract

An anti-collusive vote weighting method and system. Instances of possible vote collusion may be identified based on correlating the vote history of users voting on an information item and weighting the votes in accordance with the correlated voting history. A list of information items may be compiled and ranked by the quantity of voting data received from a plurality of users. The vote histories of two or more users may be correlated to obtain a correlation value associated with the users. A lesser predetermined weight may be applied to the voting data of users having correlation values above a first predetermined value. In addition, a greater predetermined weight may be applied to the voting data of users having correlation values below a second predetermined value. The greater the correlation between vote histories of users, the greater the likelihood that the voters are colluding to vote for the information item.

Claims

1. An anti-collusive vote weighting system comprising:

a network interface disposed to receive voting data from a plurality of users, the voting data pertaining to information items;

a database comprising vote histories for the users, the vote histories associating each user with voting data;

a memory holding program instructions operable for;

compiling a list of information items ranked by the quantity of voting data received from the plurality of users above a predetermined threshold;

correlating the vote histories of two or more users for each one of the information items to obtain a correlation value associated for each one of the two or more users;

assigning a lesser predetermined weight to the voting data of users having correlation values above a first predetermined value; and

a processor, in communication with the memory and the network interface, configured for operating the program instructions.

2. The anti-collusive vote weighting system of claim 1, the memory further holding program instructions operable for aggregating the voting data from users associated with each one of the information items.

3. The anti-collusive vote weighting system of claim 2, the memory further holding program instructions operable for outputting an adjusted voter score for each one of the information items.

4. The anti-collusive vote weighting system of claim 1, wherein the list is pre-populated.

5. The anti-collusive vote weighting system of claim 1, wherein the list is generated by user submissions.

6. The anti-collusive vote weighting system of claim 1, wherein the list ranks information items from the highest quantity of voting data received to the lowest quantity of voting data received.

7. The anti-collusive vote weighting system of claim 1, wherein the program instructions further comprise instructions for identifying two or more information items concerning identical topics by analyzing any one or more of the title, contents or source of the information items.

8. The anti-collusive vote weighting system of claim 1, wherein the lesser predetermined weight assigned to voting data of each user is based on the correlation value associated with the user.

9. The anti-collusive vote weighting system of claim 1 further comprising assigning a greater predetermined weight to the voting data of the users having correlation values below a second predetermined value.

10. The anti-collusive vote weighting system of claim 9, wherein the greater predetermined weight assigned to the voting data of each user is based on the correlation value associated with the user.

11. Computer-readable media encoded with instructions operative to cause a computer to perform the steps of:

compiling information items ranked by the quantity of voting data received from a plurality of users;

correlating vote histories of two or more users for each one of the information items to obtain a correlation value for each one of the two or more users, representing a frequency with which the two or more users have provided identical votes for information items that are identical or having identical topics;

assigning a lesser predetermined weight to the voting data of users having correlation values above a first predetermined value, to provide a weighted ranking of the information items; and

providing an output for display of the information items organized according to the weighted ranking, thereby reducing impact of collaborative voting on ranking of the information items.

12. The computer-readable media of claim 11, further comprising selecting the information items to include in the ranked output.

13. The computer-readable media of claim 11, further comprising selecting the information items to include in the ranked output from information items submitted by users.

14. The computer-readable media of claim 11 further operative to provide the output for display of the information items organized in a list.

15. The computer-readable media of claim 14, wherein the list ranks information items from the highest quantity of voting data received to the lowest quantity of voting data received.

16. The computer-readable media of claim 11 further operative to perform identifying the information items having identical topics by analyzing any one or more of the title, contents or source of the information items.

17. The computer-readable media of claim 11 further operative to perform the step of assigning a greater predetermined weight to the voting data of the users having correlation values below a second predetermined value.

18. A method for reducing impact of collaborative user responses on data structures organized according to collective interest indicated by responses received from a plurality of clients, the method comprising:

compiling interest data for electronic information items at a server, the interest data compiled from responses originating from a plurality of clients;

correlating response histories of two or more accounts for each one of the information items to obtain a correlation score for each one of the two or more accounts, representing a degree to which the two or more accounts are sources of identical responses for information items that are substantially identical or that concern substantially identical topics;

weighting the interest data to reduce influence of responses received from the plurality of clients in inverse proportion to each accounts'"'"' correlation score; and

providing an output for display of the information items organized according to the weighted interest data at client display terminals, thereby reducing influence of collaborative voting on relative interest indicated in the display for the information items.

19. The method of claim 18, further comprising selecting the information items to include in the output, based on the interest data.

20. The method of claim 18, further comprising selecting the information items to include in the ranked output from information items submitted via the plurality of clients.

21. The method of claim 18, further comprising providing the output for display of the information items organized in a ranked list.

22. The method of claim 21, wherein the list ranks information items from a highest interest level indicated by the weighted interest data to a lowest interest level indicated by the weighted interest data.

23. The method of claim 18, further comprising identifying the information items having identical topics by analyzing any one or more of the title, contents or source of the information items.