System and method for facilitating interactive selection of clusters and presentation of related datasets

• US 8,051,082 B2
• Filed: 12/19/2006
• Issued: 11/01/2011
• Est. Priority Date: 12/19/2006
• Status: Active Grant

• Current Assignee: R2 Solutions LLC (Acacia Research Corporation)
• Original Assignee: Yahoo! Inc. (Apollo Global Management, Inc.)
• Inventors: Burgess, David A., Shanbbag, Amit Umesh, Ames, Glen Anthony, Koran, Joshua M.
• Primary Examiner(s): Trujillo; James
• Assistant Examiner(s): Spieler; William
• Application Number:
  US11/642,444
• Publication Number:
  US 20080147591A1
• Time in Patent Office: 1,778 Days
• Field of Search: 707/4, 707/737
• US Class Current: 707/737
• CPC Class Codes: G06F 16/2423 Interactive query statement specification based on a database schema
• CPC Class Codes: G06F 16/2465 Query processing support for facilitating data mining operations in structured databases

Abstract

A system and method to facilitate interactive selection of groupings of clusters and presentation of related datasets are described. An interactive data interface is presented to a user in a display window, the interactive data interface configured to display multiple alternate groupings of clusters associated with at least one dataset of records targeted by the user. Selection of a grouping of clusters from the plurality of selectable groupings is further facilitated based on one or more predetermined parameters associated with each grouping of clusters and the individual clusters within a respective grouping, such as, for example, a target ratio value and a target count value corresponding to each cluster of records.

Claims

1. A computer-implemented method comprising:

receiving, at a computer, a plurality of clusters associated with at least one dataset of records possessing dataset attributes, and a plurality of user-specified attributes wherein the user-specified attributes denote values corresponding to the dataset attributes;

determining, using a computer, a target ratio for each of the clusters, wherein the target ratio comprises a number of records that possess the user specified attributes within each cluster divided by a total number of records within each cluster;

determining, using a computer, a target count for each of the clusters, wherein the target count comprises the number of records that possess the user specified attributes within each cluster;

receiving, at a computer, a user defined weight; and

determining, in a computer, an optimal grouping of clusters using at least one of;

an average function, wherein the average function incorporates the target ratio, the target count, and the user-defined weight, and

a maximization function, wherein the maximization function incorporates the target ratio, the target count, and the user-defined weight.

2. The computer-implemented method according to claim 1, further comprising:

presenting an interactive data interface to a user in a display window, said interactive data interface displaying a plurality of groupings of said clusters associated with at least one dataset of records targeted by said user;

selecting a grouping from said groupings of said clusters based on at least one predetermined parameter associated with each grouping of clusters within said plurality of groupings and displayed within said interactive data interface;

retrieving said plurality of groupings of said clusters from a data storage module in response to a data request from said user; and

retrieving parameter values associated with said at least one predetermined parameter from said data storage module in response to said data request.

3. The computer-implemented method according to claim 2, wherein retrieving said plurality of groupings of clusters further comprises:

selecting at least one user objective within said interactive data interface, said at least one user objective to determine said plurality of groupings of clusters displayed within said data interface.

4. The computer-implemented method according to claim 2, wherein said selecting said grouping is performed in response to a command received from said user through said interactive data interface.

5. The computer-implemented method according to claim 2, wherein said selecting further comprises:

analyzing said retrieved groupings of clusters and said parameter values to determine said selected grouping of clusters; and

facilitating indication of said selected grouping of clusters to said user within said data interface.

6. The computer-implemented method according to claim 2, wherein said at least one predetermined parameter further comprises the target ratio associated with each cluster within said selected grouping.

7. The computer-implemented method according to claim 2, wherein said at least one predetermined parameter further comprises the target count associated with each cluster within said selected grouping.

8. The computer-implemented method according to claim 2, wherein said at least one predetermined parameter further comprises the target ratio and the target count associated with each cluster within said selected grouping.

9. A system, comprising:

a data storage module to store at least one dataset of records targeted by a user; and

a processing engine coupled to said data storage module, wherein said processing engine;

receives a plurality of clusters associated with at least one dataset of records possessing dataset attributes, and a plurality of user-specified attributes wherein the user-specified attributes denote values corresponding to the dataset attributes;

determines a target ratio for each of the clusters, wherein the target ratio comprises a number of records that possess the user specified attributes within each cluster divided by a total number of records within each cluster;

determines a target count for each of the clusters, wherein the target count comprises the number of records that possess the user specified attributes within each cluster;

receives a user defined weight; and

determining an optimal grouping of clusters using at least one of;

an average function, wherein the average function incorporates the target ratio, the target count, and the user-defined weight, and

a maximization function, wherein the maximization function incorporates the target ratio, the target count, and the user-defined weight.

10. The system according to claim 9, wherein said processing engine further:

presents an interactive data interface to a user in a display window, said interactive data interface displaying a plurality of groupings of said clusters associated with at least one dataset of records targeted by said user;

selects a grouping from said groupings of said clusters based on at least one predetermined parameter associated with each grouping of clusters within said plurality of groupings and displayed within said interactive data interface;

retrieves said plurality of groupings of clusters from said data storage module in response to a data request from said user; and

retrieves parameter values associated with said at least one predetermined parameter from said data storage module in response to said data request.

11. The system according to claim 10, wherein said processing engine further selects at least one user objective within said interactive data interface, said at least one user objective to determine said plurality of groupings of clusters displayed within said data interface.

12. The system according to claim 10, wherein said processing engine further selects said grouping in response to a command received from said user through said interactive data interface.

13. The system according to claim 10, wherein said processing engine further analyzes said retrieved groupings of clusters and said parameter values to determine said selected grouping of clusters, and facilitates indication of said selected grouping of clusters to said user within said data interface.

14. The system according to claim 10, wherein said at least one predetermined parameter further comprises the target ratio associated with each cluster within said selected grouping.

15. The system according to claim 10, wherein said at least one predetermined parameter further comprises the target count associated with each cluster within said selected grouping.

16. The system according to claim 10, wherein said at least one predetermined parameter further comprises the target ratio and the target count associated with each cluster within said selected grouping.

17. A computer readable medium containing executable instructions stored thereon, which, when executed in a processing system, cause said processing system to perform a method comprising:

receiving, at a computer, a plurality of clusters associated with at least one dataset of records possessing dataset attributes, and a plurality of user-specified attributes wherein the user-specified attributes denote values corresponding to the dataset attributes;

determining, using a computer, a target ratio for each of the clusters, wherein the target ratio comprises a number of records that possess the user specified attributes within each cluster divided by a total number of records within each cluster;

determining, using a computer, a target count for each of the clusters, wherein the target count comprises the number of records that possess the user specified attributes within each cluster;

receiving, at a computer, a user defined weight; and

determining an optimal grouping of clusters using at least one of;

an average function, wherein the average function incorporates the target ratio, the target count, and the user-defined weight, and

a maximization function, wherein the maximization function incorporates the target ratio, the target count, and the user-defined weight.

18. The computer readable medium according to claim 17, wherein said method further comprises:

presenting an interactive data interface to a user in a display window, said interactive data interface displaying a plurality of groupings of said clusters associated with at least one dataset of records targeted by said user;

selecting a grouping from said groupings of said clusters based on at least one predetermined parameter associated with each grouping of clusters within said plurality of groupings and displayed within said interactive data interface;

retrieving said plurality of groupings of clusters from a data storage module in response to a data request from said user; and

retrieving parameter values associated with said at least one predetermined parameter from said data storage module in response to said data request.

19. The computer readable medium according to claim 18, wherein retrieving said plurality of groupings of clusters further comprises:

selecting at least one user objective within said interactive data interface, said at least one user objective to determine said plurality of groupings of clusters displayed within said data interface.

20. The computer readable medium according to claim 18, wherein said selecting said grouping is performed in response to a command received from said user through said interactive data interface.

21. The computer readable medium according to claim 18, wherein said selecting further comprises:

analyzing said retrieved groupings of clusters and said parameter values to determine said selected grouping of clusters; and

facilitating indication of said selected grouping of clusters to said user within said data interface.

22. The computer readable medium according to claim 17, wherein said at least one predetermined parameter further comprises the target ratio associated with each cluster within said selected grouping.

23. The computer readable medium according to claim 17, wherein said at least one predetermined parameter further comprises the target count associated with each cluster within said selected grouping.

24. The computer readable medium according to claim 17, wherein said at least one predetermined parameter further comprises the target ratio and the target count associated with each cluster within said selected grouping.