ADAPTIVE USER FEEDBACK WINDOW

• US 20090276729A1
• Filed: 04/30/2008
• Published: 11/05/2009
• Est. Priority Date: 04/30/2008
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Cantu-Paz, Erick
• Granted Patent: US 8,332,775 B2
• Time in Patent Office: Days
• US Class Current: 715/811
• CPC Class Codes: G06F 16/954 Navigation, e.g. using categorised browsing

Abstract

The subject matter disclosed herein relates to maintaining a history of user interaction data within a sliding window, where the sliding window may be sized based at least in part on a quantification of such user interaction.

Claims

1. A method, comprising:

collecting data regarding user interaction with one or more electronic documents;

maintaining a history of said data within a sliding window, wherein said sliding window is sized based at least in part on a quantification of said user interaction; and

transmitting a search result to a user based at least in part on said history.

2. The method of claim 1, wherein said quantification of said user interaction comprises user impressions of said electronic documents, and wherein said window is sized to include at least a desired number of impressions.

3. The method of claim 1, wherein said sliding window is further sized based at least in part on a change in said user interaction that exceeds a threshold value.

4. The method of claim 1, wherein said sliding window is further sized based at least in part on a change in said user interaction that exceeds a threshold value, and wherein said change in user interaction comprises a change in click through rate.

5. The method of claim 1, wherein said sliding window is further sized based at least in part on a maximum time frame.

6. The method of claim 1, wherein said sliding window is further sized based at least in part on a maximum and minimum time frame.

7. The method of claim 1, further comprising collapsing at least a portion of history of said data.

8. The method of claim 1, further comprising collapsing at least a portion of history of said data, wherein said history comprises at least one node containing data collapsed together from two or more other nodes.

9. The method of claim 1, wherein said electronic document comprises a web page.

10. An article comprising:

a storage medium comprising machine-readable instructions stored thereon which, if executed direct a computing platform to;

collect data regarding user interaction with one or more electronic documents;

maintain a history of said data within a sliding window, wherein said sliding window is sized based at least in part on a quantification of said user interaction; and

transmit a search result to a user based at least in part on said history.

11. The article of claim 10, wherein said quantification of said user interaction comprises user impressions of said electronic documents, and wherein said window is sized to include at least a desired number of impressions.

12. The article of claim 10, wherein said sliding window is further sized based at least in part on a change in said user interaction that exceeds a threshold value.

13. The article of claim 10, wherein said sliding window is further sized based at least in part on a change in said user interaction that exceeds a threshold value, and wherein said change in user interaction comprises a change in click through rate.

14. The article of claim 10, wherein said sliding window is further sized based at least in part on a maximum time frame.

15. The article of claim 10, wherein said sliding window is further sized based at least in part on a maximum and minimum time frame.

16. The article of claim 10, wherein said machine-readable instructions, if executed, further direct a computing platform to collapse at least a portion of history of said data, wherein said history comprises at least one node containing data collapsed together from two or more other nodes.

17. An apparatus comprising:

a computing platform, said computing platform being adapted to;

collect data regarding user interaction with one or more electronic documents;

maintain a history of said data within a sliding window, wherein said sliding window is sized based at least in part on a quantification of said user interaction; and

transmit a search result to a user based at least in part on said history.

18. The apparatus of claim 17, wherein said quantification of said user interaction comprises user impressions of said electronic documents, and wherein said window is sized to include at least a desired number of impressions.

19. The apparatus of claim 17, wherein said sliding window is further sized based at least in part on a change in said user interaction that exceeds a threshold value, and wherein said change in user interaction comprises a change in click through rate.

20. The apparatus of claim 17, wherein said computing platform is further adapted to collapse at least a portion of history of said data, wherein said history comprises at least one node containing data collapsed together from two or more other nodes.

21. The apparatus of claim 17, wherein said computing platform is further adapted to:

collapse at least a portion of history of said data, wherein said history comprises at least one node containing data collapsed together from two or more other nodes;

wherein said quantification of said user interaction comprises user impressions of said electronic documents, and wherein said window is sized to include at least a desired number of impressions;

wherein said sliding window is further sized based at least in part on a maximum and minimum time frame;

wherein said sliding window is further sized based at least in part on a maximum time frame; and

wherein said sliding window is further sized based at least in part on a change in said user interaction that exceeds a threshold value, and wherein said change in user interaction comprises a change in click through rate.